[1]
|
A survey on recent trends in deep learning for nucleus segmentation from histopathology images
Evolving Systems,
2024
DOI:10.1007/s12530-023-09491-3
|
|
|
[2]
|
Analysis of Liver Tumor Segmentation using Deep ResUNet
2023 Third International Conference on Artificial Intelligence and Smart Energy (ICAIS),
2023
DOI:10.1109/ICAIS56108.2023.10073676
|
|
|
[3]
|
Diffusion models in bioinformatics and computational biology
Nature Reviews Bioengineering,
2023
DOI:10.1038/s44222-023-00114-9
|
|
|
[4]
|
Follow-up of liver metastases: a comparison of deep learning and RECIST 1.1
European Radiology,
2023
DOI:10.1007/s00330-023-09926-0
|
|
|
[5]
|
Convolutional neural network-based classifiers for liver tumor detection using computed tomography scans
Innovations in Systems and Software Engineering,
2023
DOI:10.1007/s11334-023-00547-w
|
|
|
[6]
|
Artificial intelligence: A review of current applications in hepatocellular carcinoma imaging
Diagnostic and Interventional Imaging,
2023
DOI:10.1016/j.diii.2022.10.001
|
|
|
[7]
|
Robust End-to-End Focal Liver Lesion Detection Using Unregistered Multiphase Computed Tomography Images
IEEE Transactions on Emerging Topics in Computational Intelligence,
2023
DOI:10.1109/TETCI.2021.3132382
|
|
|
[8]
|
EMED-UNet: An Efficient Multi-Encoder-Decoder Based UNet for Medical Image Segmentation
IEEE Access,
2023
DOI:10.1109/ACCESS.2023.3309158
|
|
|
[9]
|
An improved 3D KiU-Net for segmentation of liver tumor
Computers in Biology and Medicine,
2023
DOI:10.1016/j.compbiomed.2023.107006
|
|
|
[10]
|
WSNet: Towards An Effective Method for Wound Image Segmentation
2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV),
2023
DOI:10.1109/WACV56688.2023.00325
|
|
|
[11]
|
Basics of Image Processing
Imaging Informatics for Healthcare Professionals,
2023
DOI:10.1007/978-3-031-48446-9_3
|
|
|
[12]
|
Artificial intelligence: A review of current applications in hepatocellular carcinoma imaging
Diagnostic and Interventional Imaging,
2023
DOI:10.1016/j.diii.2022.10.001
|
|
|
[13]
|
WSNet: Towards An Effective Method for Wound Image Segmentation
2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV),
2023
DOI:10.1109/WACV56688.2023.00325
|
|
|
[14]
|
A survey on recent trends in deep learning for nucleus segmentation from histopathology images
Evolving Systems,
2023
DOI:10.1007/s12530-023-09491-3
|
|
|
[15]
|
Hepatic vessels segmentation using deep learning and preprocessing enhancement
Journal of Applied Clinical Medical Physics,
2023
DOI:10.1002/acm2.13966
|
|
|
[16]
|
Analysis of Liver Tumor Segmentation using Deep ResUNet
2023 Third International Conference on Artificial Intelligence and Smart Energy (ICAIS),
2023
DOI:10.1109/ICAIS56108.2023.10073676
|
|
|
[17]
|
Robust End-to-End Focal Liver Lesion Detection Using Unregistered Multiphase Computed Tomography Images
IEEE Transactions on Emerging Topics in Computational Intelligence,
2023
DOI:10.1109/TETCI.2021.3132382
|
|
|
[18]
|
Deep Federated Machine Learning-Based Optimization Methods for Liver Tumor Diagnosis: A Review
Archives of Computational Methods in Engineering,
2023
DOI:10.1007/s11831-023-09901-4
|
|
|
[19]
|
Liver lesion changes analysis in longitudinal CECT scans by simultaneous deep learning voxel classification with SimU-Net
Medical Image Analysis,
2023
DOI:10.1016/j.media.2022.102675
|
|
|
[20]
|
GL-Segnet: Global-Local representation learning net for medical image segmentation
Frontiers in Neuroscience,
2023
DOI:10.3389/fnins.2023.1153356
|
|
|
[21]
|
A novel lung tumor detection technique using Fast Greedy Snake algorithm
PROCEEDING OF INTERNATIONAL CONFERENCE ON ENERGY, MANUFACTURE, ADVANCED MATERIAL AND MECHATRONICS 2021,
2023
DOI:10.1063/5.0126492
|
|
|
[22]
|
Semantic Segmentation for Various Applications: Research Contribution and Comprehensive Review
INTERACT 2023,
2023
DOI:10.3390/engproc2023032021
|
|
|
[23]
|
Liver lesion changes analysis in longitudinal CECT scans by simultaneous deep learning voxel classification with SimU-Net
Medical Image Analysis,
2023
DOI:10.1016/j.media.2022.102675
|
|
|
[24]
|
Establishment and Test Effect of Artificial Intelligence Optimization Model Based on Convolutional Neural Network
Journal of Mathematics,
2023
DOI:10.1155/2023/4216012
|
|
|
[25]
|
An improved 3D KiU-Net for segmentation of liver tumor
Computers in Biology and Medicine,
2023
DOI:10.1016/j.compbiomed.2023.107006
|
|
|
[26]
|
Deep Federated Machine Learning-Based Optimization Methods for Liver Tumor Diagnosis: A Review
Archives of Computational Methods in Engineering,
2023
DOI:10.1007/s11831-023-09901-4
|
|
|
[27]
|
Intelligent Hepatocellular Carcinoma Detection using Hybrid Radial basis Function Networks
2023 7th International Conference on Intelligent Computing and Control Systems (ICICCS),
2023
DOI:10.1109/ICICCS56967.2023.10142770
|
|
|
[28]
|
Recognition of Diffuse Hepatic Steatosis
2023 33rd Conference of Open Innovations Association (FRUCT),
2023
DOI:10.23919/FRUCT58615.2023.10143062
|
|
|
[29]
|
Deep Learning Algorithm for Differentiating Patients with a Healthy Liver from Patients with Liver Lesions Based on MR Images
Cancers,
2023
DOI:10.3390/cancers15123142
|
|
|
[30]
|
Improving liver lesions classification on CT/MRI images based on Hounsfield Units attenuation and deep learning
Gene Expression Patterns,
2023
DOI:10.1016/j.gep.2022.119289
|
|
|
[31]
|
Deep Learning Applications in Image Analysis
Studies in Big Data,
2023
DOI:10.1007/978-981-99-3784-4_10
|
|
|
[32]
|
Severity Quantification of COVID-19 Infection using ResDense U-net in Chest X-ray
2023 5th International Conference on Bio-engineering for Smart Technologies (BioSMART),
2023
DOI:10.1109/BioSMART58455.2023.10162077
|
|
|
[33]
|
Follow-up of liver metastases: a comparison of deep learning and RECIST 1.1
European Radiology,
2023
DOI:10.1007/s00330-023-09926-0
|
|
|
[34]
|
Automated Segmentation of Levator Ani Muscle from 3D Endovaginal Ultrasound Images
Bioengineering,
2023
DOI:10.3390/bioengineering10080894
|
|
|
[35]
|
A Coarse-to-Fine Fusion Network for Small Liver Tumor Detection and Segmentation: A Real-World Study
Diagnostics,
2023
DOI:10.3390/diagnostics13152504
|
|
|
[36]
|
Improving liver lesions classification on CT/MRI images based on Hounsfield Units attenuation and deep learning
Gene Expression Patterns,
2023
DOI:10.1016/j.gep.2022.119289
|
|
|
[37]
|
Liver CT Image Recognition Method Based on Capsule Network
Information,
2023
DOI:10.3390/info14030183
|
|
|
[38]
|
Improving liver lesions classification on CT/MRI images based on Hounsfield Units attenuation and deep learning
Gene Expression Patterns,
2023
DOI:10.1016/j.gep.2022.119289
|
|
|
[39]
|
Automated liver tissues delineation techniques: A systematic survey on machine learning current trends and future orientations
Engineering Applications of Artificial Intelligence,
2023
DOI:10.1016/j.engappai.2022.105532
|
|
|
[40]
|
Liver lesion changes analysis in longitudinal CECT scans by simultaneous deep learning voxel classification with SimU-Net
Medical Image Analysis,
2023
DOI:10.1016/j.media.2022.102675
|
|
|
[41]
|
Liver lesion changes analysis in longitudinal CECT scans by simultaneous deep learning voxel classification with SimU-Net
Medical Image Analysis,
2023
DOI:10.1016/j.media.2022.102675
|
|
|
[42]
|
Efficient two-step liver and tumour segmentation on abdominal CT via deep learning and a conditional random field
Computers in Biology and Medicine,
2022
DOI:10.1016/j.compbiomed.2022.106076
|
|
|
[43]
|
Autism spectrum disorder analysis by using a 3D-ResNet-based approach
Fourteenth International Conference on Digital Image Processing (ICDIP 2022),
2022
DOI:10.1117/12.2644315
|
|
|
[44]
|
Deep learning techniques for liver and liver tumor segmentation: A review
Computers in Biology and Medicine,
2022
DOI:10.1016/j.compbiomed.2022.105620
|
|
|
[45]
|
Liver Cancer Detection and Classification Using Raspberry Pi
Journal of Medical Imaging and Health Informatics,
2022
DOI:10.1166/jmihi.2022.3941
|
|
|
[46]
|
Improved Salp Swarm Optimization-based Fuzzy Centroid Region Growing for Liver Tumor Segmentation and Deep Learning Oriented Classification
International Journal of Next-Generation Computing,
2022
DOI:10.47164/ijngc.v13i5.902
|
|
|
[47]
|
Artificial intelligence: A review of current applications in hepatocellular carcinoma imaging
Diagnostic and Interventional Imaging,
2022
DOI:10.1016/j.diii.2022.10.001
|
|
|
[48]
|
Deep learning techniques for liver and liver tumor segmentation: A review
Computers in Biology and Medicine,
2022
DOI:10.1016/j.compbiomed.2022.105620
|
|
|
[49]
|
Role of artificial intelligence in the diagnosis and treatment of hepatocellular carcinoma
Artificial Intelligence in Gastroenterology,
2022
DOI:10.35712/aig.v3.i4.96
|
|
|
[50]
|
Deep Learning Hybrid Techniques for Brain Tumor Segmentation
Sensors,
2022
DOI:10.3390/s22218201
|
|
|
[51]
|
Efficient two-step liver and tumour segmentation on abdominal CT via deep learning and a conditional random field
Computers in Biology and Medicine,
2022
DOI:10.1016/j.compbiomed.2022.106076
|
|
|
[52]
|
Federated Learning for Healthcare Domain - Pipeline, Applications and Challenges
ACM Transactions on Computing for Healthcare,
2022
DOI:10.1145/3533708
|
|
|
[53]
|
Deep learning for image-based liver analysis — A comprehensive review focusing on malignant lesions
Artificial Intelligence in Medicine,
2022
DOI:10.1016/j.artmed.2022.102331
|
|
|
[54]
|
Automated Tumor Segmentation in Radiotherapy
Seminars in Radiation Oncology,
2022
DOI:10.1016/j.semradonc.2022.06.002
|
|
|
[55]
|
Research Anthology on Improving Medical Imaging Techniques for Analysis and Intervention
2022
DOI:10.4018/978-1-6684-7544-7.ch059
|
|
|
[56]
|
Liver tumor segmentation from computed tomography images using
multiscale
residual dilated
encoder‐decoder
network
International Journal of Imaging Systems and Technology,
2022
DOI:10.1002/ima.22640
|
|
|
[57]
|
Hybrid‐attention densely connected U‐Net with GAP for extracting livers from CT volumes
Medical Physics,
2022
DOI:10.1002/mp.15435
|
|
|
[58]
|
Cancer diagnosis using artificial intelligence: a review
Artificial Intelligence Review,
2022
DOI:10.1007/s10462-021-10074-4
|
|
|
[59]
|
A lung tumor detection technique using gradient vector flow algorithm
EIGHTH INTERNATIONAL CONFERENCE NEW TRENDS IN THE APPLICATIONS OF DIFFERENTIAL EQUATIONS IN SCIENCES (NTADES2021),
2022
DOI:10.1063/5.0072457
|
|
|
[60]
|
Study of deep learning techniques for medical image analysis: A review
Materials Today: Proceedings,
2022
DOI:10.1016/j.matpr.2022.01.071
|
|
|
[61]
|
A computer-aided diagnostic system for liver tumor detection using modified U-Net architecture
The Journal of Supercomputing,
2022
DOI:10.1007/s11227-021-04266-6
|
|
|
[62]
|
Liver surgery for colorectal metastasis: New paths and new goals with the help of artificial intelligence
Artificial Intelligence in Gastroenterology,
2022
DOI:10.35712/aig.v3.i2.28
|
|
|
[63]
|
Liver tumor segmentation using a new asymmetrical dilated convolutional semantic segmentation network in
CT
images
International Journal of Imaging Systems and Technology,
2022
DOI:10.1002/ima.22663
|
|
|
[64]
|
Automatic Detection of Brain Tumor from CT and MRI Images using Wireframe model and 3D Alex-Net
2022 International Conference on Decision Aid Sciences and Applications (DASA),
2022
DOI:10.1109/DASA54658.2022.9765114
|
|
|
[65]
|
Detection of Liver Cancer through Computed Tomography Images using Deep Convolutional Neural Networks
2022 2nd International Conference on Digital Futures and Transformative Technologies (ICoDT2),
2022
DOI:10.1109/ICoDT255437.2022.9787429
|
|
|
[66]
|
Efficient Local Cloud-Based Solution for Liver Cancer Detection Using Deep Learning
International Journal of Cloud Applications and Computing,
2022
DOI:10.4018/IJCAC.2022010109
|
|
|
[67]
|
A Deep Learning Approach for Liver and Tumor Segmentation in CT Images Using ResUNet
Bioengineering,
2022
DOI:10.3390/bioengineering9080368
|
|
|
[68]
|
Cross-spectral human behavior recognition based on deep convolutional networks for global temporal representation
Journal of Electronic Imaging,
2022
DOI:10.1117/1.JEI.32.1.011209
|
|
|
[69]
|
Optimizable Image Segmentation Method with Superpixels and Feature Migration for Aerospace Structures
Aerospace,
2022
DOI:10.3390/aerospace9080465
|
|
|
[70]
|
A review on the use of deep learning for medical images segmentation
Neurocomputing,
2022
DOI:10.1016/j.neucom.2022.07.070
|
|
|
[71]
|
An Encoder-Decoder Network for Automatic Clinical Target Volume Target Segmentation of Cervical Cancer in CT Images
International Journal of Crowd Science,
2022
DOI:10.26599/IJCS.2022.9100014
|
|
|
[72]
|
High precision detection of small hepatocellular carcinoma using improved EfficientNet with Self-Attention
2022 IEEE/ACIS 22nd International Conference on Computer and Information Science (ICIS),
2022
DOI:10.1109/ICIS54925.2022.9882470
|
|
|
[73]
|
Segmentation of Liver Tumor in CT Scan Using ResU-Net
Applied Sciences,
2022
DOI:10.3390/app12178650
|
|
|
[74]
|
Decision Support System for Liver Lesion Segmentation Based on Advanced Convolutional Neural Network Architectures
Bioengineering,
2022
DOI:10.3390/bioengineering9090467
|
|
|
[75]
|
Image Segmentation
2022
DOI:10.1002/9781119859048.ch9
|
|
|
[76]
|
Data Engineering for Smart Systems
Lecture Notes in Networks and Systems,
2022
DOI:10.1007/978-981-16-2641-8_56
|
|
|
[77]
|
Fully Automatic Knee Bone Detection and Segmentation on Three-Dimensional MRI
Diagnostics,
2022
DOI:10.3390/diagnostics12010123
|
|
|
[78]
|
Automatic deep learning system for COVID-19 infection quantification in chest CT
Multimedia Tools and Applications,
2022
DOI:10.1007/s11042-021-11299-9
|
|
|
[79]
|
RMS-UNet: Residual multi-scale UNet for liver and lesion segmentation
Artificial Intelligence in Medicine,
2022
DOI:10.1016/j.artmed.2021.102231
|
|
|
[80]
|
FireNet-MLstm for classifying liver lesions by using deep features in CT images
Multimedia Tools and Applications,
2022
DOI:10.1007/s11042-021-11411-z
|
|
|
[81]
|
Multi-Task Deep Learning Approach for Simultaneous Objective Response Prediction and Tumor Segmentation in HCC Patients with Transarterial Chemoembolization
Journal of Personalized Medicine,
2022
DOI:10.3390/jpm12020248
|
|
|
[82]
|
Approaches and Applications of Deep Learning in Virtual Medical Care
Advances in Healthcare Information Systems and Administration,
2022
DOI:10.4018/978-1-7998-8929-8.ch001
|
|
|
[83]
|
Early Prediction of Sepsis Onset Using Neural Architecture Search Based on Genetic Algorithms
International Journal of Environmental Research and Public Health,
2022
DOI:10.3390/ijerph19042349
|
|
|
[84]
|
Grayscale medical image segmentation method based on 2D&3D object detection with deep learning
BMC Medical Imaging,
2022
DOI:10.1186/s12880-022-00760-2
|
|
|
[85]
|
Medical image segmentation using deep learning: A survey
IET Image Processing,
2022
DOI:10.1049/ipr2.12419
|
|
|
[86]
|
Image Segmentation
2022
DOI:10.1002/9781119859048.ch9
|
|
|
[87]
|
A review on the use of deep learning for medical images segmentation
Neurocomputing,
2022
DOI:10.1016/j.neucom.2022.07.070
|
|
|
[88]
|
A review on the use of deep learning for medical images segmentation
Neurocomputing,
2022
DOI:10.1016/j.neucom.2022.07.070
|
|
|
[89]
|
Deep Learning-Based Cancer Detection-Recent Developments, Trend and Challenges
Computer Modeling in Engineering & Sciences,
2022
DOI:10.32604/cmes.2022.018418
|
|
|
[90]
|
Automatic Liver Tumor Segmentation in CT Modalities Using MAT-ACM
Computer Systems Science and Engineering,
2022
DOI:10.32604/csse.2022.024788
|
|
|
[91]
|
RMS-UNet: Residual multi-scale UNet for liver and lesion segmentation
Artificial Intelligence in Medicine,
2022
DOI:10.1016/j.artmed.2021.102231
|
|
|
[92]
|
Federated Learning for Healthcare Domain - Pipeline, Applications and Challenges
ACM Transactions on Computing for Healthcare,
2022
DOI:10.1145/3533708
|
|
|
[93]
|
Preoperative diagnosis of hepatocellular carcinoma patients with bile duct tumor thrombus using deep learning method
JUSTC,
2022
DOI:10.52396/JUSTC-2022-0057
|
|
|
[94]
|
Hybrid‐attention densely connected U‐Net with GAP for extracting livers from CT volumes
Medical Physics,
2022
DOI:10.1002/mp.15435
|
|
|
[95]
|
Efficient two-step liver and tumour segmentation on abdominal CT via deep learning and a conditional random field
Computers in Biology and Medicine,
2022
DOI:10.1016/j.compbiomed.2022.106076
|
|
|
[96]
|
Deep learning techniques for liver and liver tumor segmentation: A review
Computers in Biology and Medicine,
2022
DOI:10.1016/j.compbiomed.2022.105620
|
|
|
[97]
|
MVDI25K: A large-scale dataset of microscopic vaginal discharge images
BenchCouncil Transactions on Benchmarks, Standards and Evaluations,
2021
DOI:10.1016/j.tbench.2021.100008
|
|
|
[98]
|
Deep Learning for Cancer Diagnosis
Studies in Computational Intelligence,
2021
DOI:10.1007/978-981-15-6321-8_3
|
|
|
[99]
|
An automated slice sorting technique for multi-slice computed tomography liver cancer images using convolutional network
Expert Systems with Applications,
2021
DOI:10.1016/j.eswa.2021.115686
|
|
|
[100]
|
Current Status of Radiomics and Deep Learning in Liver Imaging
Journal of Computer Assisted Tomography,
2021
DOI:10.1097/RCT.0000000000001169
|
|
|
[101]
|
An adaptive learning method of anchor shape priors for biological cells detection and segmentation
Computer Methods and Programs in Biomedicine,
2021
DOI:10.1016/j.cmpb.2021.106260
|
|
|
[102]
|
Efficient Local Cloud-Based Solution for Liver Cancer Detection Using Deep Learning
International Journal of Cloud Applications and Computing,
2021
DOI:10.4018/IJCAC.2022010109
|
|
|
[103]
|
Liver-Tumor Detection Using CNN ResUNet
Computers, Materials & Continua,
2021
DOI:10.32604/cmc.2021.015151
|
|
|
[104]
|
Interactive medical image segmentation via a point-based interaction
Artificial Intelligence in Medicine,
2021
DOI:10.1016/j.artmed.2020.101998
|
|
|
[105]
|
Efficient Local Cloud-Based Solution for Liver Cancer Detection Using Deep Learning
International Journal of Cloud Applications and Computing,
2021
DOI:10.4018/IJCAC.2022010109
|
|
|
[106]
|
GA-UNet: UNet-based framework for segmentation of 2D and 3D medical images applicable on heterogeneous datasets
Neural Computing and Applications,
2021
DOI:10.1007/s00521-021-06134-z
|
|
|
[107]
|
An automated slice sorting technique for multi-slice computed tomography liver cancer images using convolutional network
Expert Systems with Applications,
2021
DOI:10.1016/j.eswa.2021.115686
|
|
|
[108]
|
An Efficient Approach for Gastric Polyps Detection Based on Improved SSD
2021 China Automation Congress (CAC),
2021
DOI:10.1109/CAC53003.2021.9727723
|
|
|
[109]
|
A semantic segmentation algorithm supported by image processing and neural network
2021 IEEE International Conference on Emergency Science and Information Technology (ICESIT),
2021
DOI:10.1109/ICESIT53460.2021.9696835
|
|
|
[110]
|
Attention Convolutional U-Net for Automatic Liver Tumor Segmentation
2021 International Conference on Frontiers of Information Technology (FIT),
2021
DOI:10.1109/FIT53504.2021.00028
|
|
|
[111]
|
MVDI25K: A large-scale dataset of microscopic vaginal discharge images
BenchCouncil Transactions on Benchmarks, Standards and Evaluations,
2021
DOI:10.1016/j.tbench.2021.100008
|
|
|
[112]
|
Predicting the Prognosis of MCI Patients Using Longitudinal MRI Data
IEEE/ACM Transactions on Computational Biology and Bioinformatics,
2021
DOI:10.1109/TCBB.2020.3017872
|
|
|
[113]
|
An automated slice sorting technique for multi-slice computed tomography liver cancer images using convolutional network
Expert Systems with Applications,
2021
DOI:10.1016/j.eswa.2021.115686
|
|
|
[114]
|
Application of Neural Networks for Detection of Sexual Harassment in Workspace
2021 International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT),
2021
DOI:10.1109/ICAECT49130.2021.9392429
|
|
|
[115]
|
Research Progress of Gliomas in Machine Learning
Cells,
2021
DOI:10.3390/cells10113169
|
|
|
[116]
|
TwinLiverNet: Predicting TACE Treatment Outcome from CT scans for Hepatocellular Carcinoma using Deep Capsule Networks
2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC),
2021
DOI:10.1109/EMBC46164.2021.9630913
|
|
|
[117]
|
A systematic review of the automatic kidney segmentation methods in abdominal images
Biocybernetics and Biomedical Engineering,
2021
DOI:10.1016/j.bbe.2021.10.006
|
|
|
[118]
|
Brain Tumor Detection Using Various Deep Learning Algorithms
2021 International Conference on Science & Contemporary Technologies (ICSCT),
2021
DOI:10.1109/ICSCT53883.2021.9642649
|
|
|
[119]
|
Anatomy-aided deep learning for medical image segmentation: a review
Physics in Medicine & Biology,
2021
DOI:10.1088/1361-6560/abfbf4
|
|
|
[120]
|
Six application scenarios of artificial intelligence in the precise diagnosis and treatment of liver cancer
Artificial Intelligence Review,
2021
DOI:10.1007/s10462-021-10023-1
|
|
|
[121]
|
Image Segmentation in 3D Brachytherapy Using Convolutional LSTM
Journal of Medical and Biological Engineering,
2021
DOI:10.1007/s40846-021-00624-0
|
|
|
[122]
|
Intelligent Computing
Lecture Notes in Networks and Systems,
2021
DOI:10.1007/978-3-030-80129-8_2
|
|
|
[123]
|
Effects of Multiple Filters on Liver Tumor Segmentation From CT Images
Frontiers in Oncology,
2021
DOI:10.3389/fonc.2021.697178
|
|
|
[124]
|
Advances in Artificial Intelligence, Computation, and Data Science
Computational Biology,
2021
DOI:10.1007/978-3-030-69951-2_8
|
|
|
[125]
|
An adaptive learning method of anchor shape priors for biological cells detection and segmentation
Computer Methods and Programs in Biomedicine,
2021
DOI:10.1016/j.cmpb.2021.106260
|
|
|
[126]
|
GA-UNet: UNet-based framework for segmentation of 2D and 3D medical images applicable on heterogeneous datasets
Neural Computing and Applications,
2021
DOI:10.1007/s00521-021-06134-z
|
|
|
[127]
|
Volumetric CT Texture Analysis of Intrahepatic Mass-Forming Cholangiocarcinoma for the Prediction of Postoperative Outcomes: Fully Automatic Tumor Segmentation Versus Semi-Automatic Segmentation
Korean Journal of Radiology,
2021
DOI:10.3348/kjr.2021.0055
|
|
|
[128]
|
Preliminary study of generalized semiautomatic segmentation for 3D voxel labeling of lesions based on deep learning
International Journal of Computer Assisted Radiology and Surgery,
2021
DOI:10.1007/s11548-021-02504-z
|
|
|
[129]
|
Analysis on segmentation and biomarker‐based approaches for liver cancer detection: A survey
IET Image Processing,
2021
DOI:10.1049/ipr2.12073
|
|
|
[130]
|
Proceedings of the 22nd Engineering Applications of Neural Networks Conference
Proceedings of the International Neural Networks Society,
2021
DOI:10.1007/978-3-030-80568-5_8
|
|
|
[131]
|
RETRACTED ARTICLE: Improved performance accuracy in detecting tumor in liver using deep learning techniques
Journal of Ambient Intelligence and Humanized Computing,
2021
DOI:10.1007/s12652-020-02107-7
|
|
|
[132]
|
Advances in Biomedical Engineering and Technology
Lecture Notes in Bioengineering,
2021
DOI:10.1007/978-981-15-6329-4_10
|
|
|
[133]
|
Interactive medical image segmentation via a point-based interaction
Artificial Intelligence in Medicine,
2021
DOI:10.1016/j.artmed.2020.101998
|
|
|
[134]
|
Respiratory-correlated 4D digital tomosynthesis with deep convolutional neural networks for image-guided radiation therapy
Journal of the Korean Physical Society,
2021
DOI:10.1007/s40042-020-00026-6
|
|
|
[135]
|
Current landscape and potential future applications of artificial intelligence in medical physics and radiotherapy
Artificial Intelligence in Medical Imaging,
2021
DOI:10.35711/aimi.v2.i2.37
|
|
|
[136]
|
Current Status of Radiomics and Deep Learning in Liver Imaging
Journal of Computer Assisted Tomography,
2021
DOI:10.1097/RCT.0000000000001169
|
|
|
[137]
|
A Residual-Learning-Based Multi-Scale Parallel-Convolutions- Assisted Efficient CAD System for Liver Tumor Detection
Mathematics,
2021
DOI:10.3390/math9101133
|
|
|
[138]
|
Automatic Detection and Segmentation of Liver Tumors in Multi- phase CT Images by Phase Attention Mask R-CNN
2021 IEEE International Conference on Consumer Electronics (ICCE),
2021
DOI:10.1109/ICCE50685.2021.9427760
|
|
|
[139]
|
CT Image Segmentation Method of Liver Tumor Based on Artificial Intelligence Enabled Medical Imaging
Mathematical Problems in Engineering,
2021
DOI:10.1155/2021/9919507
|
|
|
[140]
|
Deep Learning for Cancer Diagnosis
Studies in Computational Intelligence,
2021
DOI:10.1007/978-981-15-6321-8_3
|
|
|
[141]
|
Advanced Deep Learning Approach to Automatically Segment Malignant Tumors and Ablation Zone in the Liver With Contrast-Enhanced CT
Frontiers in Oncology,
2021
DOI:10.3389/fonc.2021.669437
|
|
|
[142]
|
A deep learning based review on abdominal images
Multimedia Tools and Applications,
2021
DOI:10.1007/s11042-020-09592-0
|
|
|
[143]
|
Application of artificial intelligence in the diagnosis and treatment of hepatocellular carcinoma: A review
World Journal of Gastroenterology,
2020
DOI:10.3748/wjg.v26.i37.5617
|
|
|
[144]
|
An Efficient Liver Tumor Detection using Machine Learning
2020 International Conference on Computational Science and Computational Intelligence (CSCI),
2020
DOI:10.1109/CSCI51800.2020.00130
|
|
|
[145]
|
RA-UNet: A Hybrid Deep Attention-Aware Network to Extract Liver and Tumor in CT Scans
Frontiers in Bioengineering and Biotechnology,
2020
DOI:10.3389/fbioe.2020.605132
|
|
|
[146]
|
In-Series U-Net Network to 3D Tumor Image Reconstruction for Liver Hepatocellular Carcinoma Recognition
Diagnostics,
2020
DOI:10.3390/diagnostics11010011
|
|
|
[147]
|
A deep convolutional neural network for simultaneous denoising and deblurring in computed tomography
Journal of Instrumentation,
2020
DOI:10.1088/1748-0221/15/12/P12001
|
|
|
[148]
|
$M^3$Lung-Sys: A Deep Learning System for Multi-Class Lung Pneumonia Screening from CT Imaging
IEEE Journal of Biomedical and Health Informatics,
2020
DOI:10.1109/JBHI.2020.3030853
|
|
|
[149]
|
Automatic Segmentation Using a Hybrid Dense Network Integrated With an 3D-Atrous Spatial Pyramid Pooling Module for Computed Tomography (CT) Imaging
IEEE Access,
2020
DOI:10.1109/ACCESS.2020.3024277
|
|
|
[150]
|
Comparison of Transfer Learning and Conventional Machine Learning Applied to Structural Brain MRI for the Early Diagnosis and Prognosis of Alzheimer's Disease
Frontiers in Neurology,
2020
DOI:10.3389/fneur.2020.576194
|
|
|
[151]
|
Adversarial Graph Learning and Deep Learning Techniques for improving diagnosis within CT and Ultrasound images
2020 IEEE 16th International Conference on Intelligent Computer Communication and Processing (ICCP),
2020
DOI:10.1109/ICCP51029.2020.9266242
|
|
|
[152]
|
Cascaded deep convolutional encoder-decoder neural networks for efficient liver tumor segmentation
Medical Hypotheses,
2020
DOI:10.1016/j.mehy.2019.109431
|
|
|
[153]
|
Fog Computing Employed Computer Aided Cancer Classification System Using Deep Neural Network in Internet of Things Based Healthcare System
Journal of Medical Systems,
2020
DOI:10.1007/s10916-019-1500-5
|
|
|
[154]
|
DA-Capnet: Dual Attention Deep Learning Based on U-Net for Nailfold Capillary Segmentation
IEEE Access,
2020
DOI:10.1109/ACCESS.2020.2965651
|
|
|
[155]
|
Auto-segmentation of pancreatic tumor in multi-parametric MRI using deep convolutional neural networks
Radiotherapy and Oncology,
2020
DOI:10.1016/j.radonc.2020.01.021
|
|
|
[156]
|
Liver Tumor Segmentation in CT Scans Using Modified SegNet
Sensors,
2020
DOI:10.3390/s20051516
|
|
|
[157]
|
Sağlık Alanında Veri Mahremiyetinin Korunmasına Yönelik Makine Öğrenmesi Uygulamalarına Yeni Bir Yaklaşım: Federe Öğrenme
Namık Kemal Tıp Dergisi,
2020
DOI:10.37696/nkmj.660762
|
|
|
[158]
|
Lung Cancer Prediction using Machine Learning: A Comprehensive Approach
2020 2nd International Conference on Innovative Mechanisms for Industry Applications (ICIMIA),
2020
DOI:10.1109/ICIMIA48430.2020.9074947
|
|
|
[159]
|
Automatic segmentation system for liver tumors based on the multilevel thresholding and electromagnetism optimization algorithm
International Journal of Imaging Systems and Technology,
2020
DOI:10.1002/ima.22432
|
|
|
[160]
|
Comparison of Deep-Learning and Conventional Machine-Learning Methods for the Automatic Recognition of the Hepatocellular Carcinoma Areas from Ultrasound Images
Sensors,
2020
DOI:10.3390/s20113085
|
|
|
[161]
|
Recent advancement in cancer detection using machine learning: Systematic survey of decades, comparisons and challenges
Journal of Infection and Public Health,
2020
DOI:10.1016/j.jiph.2020.06.033
|
|
|
[162]
|
Enhancing U-Net with Spatial-Channel Attention Gate for Abnormal Tissue Segmentation in Medical Imaging
Applied Sciences,
2020
DOI:10.3390/app10175729
|
|
|
[163]
|
Automatic Segmentation of Liver Tumor in Multiphase CT Images by Mask R-CNN
2020 IEEE 2nd Global Conference on Life Sciences and Technologies (LifeTech),
2020
DOI:10.1109/LifeTech48969.2020.1570619011
|
|
|
[164]
|
Deep learning and level set approach for liver and tumor segmentation from CT scans
Journal of Applied Clinical Medical Physics,
2020
DOI:10.1002/acm2.13003
|
|
|
[165]
|
Handbook of Medical Image Computing and Computer Assisted Intervention
2020
DOI:10.1016/B978-0-12-816176-0.00008-9
|
|
|
[166]
|
Handbook of Medical Image Computing and Computer Assisted Intervention
2020
DOI:10.1016/B978-0-12-816176-0.00008-9
|
|
|
[167]
|
Hybrid deep learning network for vascular segmentation in photoacoustic imaging
Biomedical Optics Express,
2020
DOI:10.1364/BOE.409246
|
|
|
[168]
|
Sparse Data–Driven Learning for Effective and Efficient Biomedical Image Segmentation
Annual Review of Biomedical Engineering,
2020
DOI:10.1146/annurev-bioeng-060418-052147
|
|
|
[169]
|
Automatic segmentation of tumors and affected organs in the abdomen using a 3D hybrid model for computed tomography imaging
Computers in Biology and Medicine,
2020
DOI:10.1016/j.compbiomed.2020.104097
|
|
|
[170]
|
Computer-aided diagnosis of liver lesions using CT images: A systematic review
Computers in Biology and Medicine,
2020
DOI:10.1016/j.compbiomed.2020.104035
|
|
|
[171]
|
Evaluation of Transfer Learning with CNN to classify the Jaw Tumors
IOP Conference Series: Materials Science and Engineering,
2020
DOI:10.1088/1757-899X/928/3/032072
|
|
|
[172]
|
Handbook of Medical Image Computing and Computer Assisted Intervention
2020
DOI:10.1016/B978-0-12-816176-0.00008-9
|
|
|
[173]
|
Deep learning and level set approach for liver and tumor segmentation from CT scans
Journal of Applied Clinical Medical Physics,
2020
DOI:10.1002/acm2.13003
|
|
|
[174]
|
Automatic segmentation system for liver tumors based on the multilevel thresholding and electromagnetism optimization algorithm
International Journal of Imaging Systems and Technology,
2020
DOI:10.1002/ima.22432
|
|
|
[175]
|
Handbook of Medical Image Computing and Computer Assisted Intervention
2020
DOI:10.1016/B978-0-12-816176-0.00008-9
|
|
|
[176]
|
Automatic Lesion Detection in Periapical X-rays
2019 International Conference on Electrical, Communication, and Computer Engineering (ICECCE),
2019
DOI:10.1109/ICECCE47252.2019.8940661
|
|
|
[177]
|
Hyper‐reflective foci segmentation in SD‐OCT retinal images with diabetic retinopathy using deep convolutional neural networks
Medical Physics,
2019
DOI:10.1002/mp.13728
|
|
|
[178]
|
Deep learning in medical imaging and radiation therapy
Medical Physics,
2019
DOI:10.1002/mp.13264
|
|
|
[179]
|
A modified scheme for liver tumor segmentation based on cascaded FCNs
Proceedings of the International Conference on Artificial Intelligence, Information Processing and Cloud Computing,
2019
DOI:10.1145/3371425.3371451
|
|
|
[180]
|
Pancreatic Segmentation via Ringed Residual U-Net
IEEE Access,
2019
DOI:10.1109/ACCESS.2019.2956550
|
|
|
[181]
|
Liver Tumor Segmentation and Subsequent Risk Prediction Based on Deeplabv3+
IOP Conference Series: Materials Science and Engineering,
2019
DOI:10.1088/1757-899X/612/2/022051
|
|
|
[182]
|
Mean of Means: An Automatic Liver Segmentation Algorithm
2019 Joint 8th International Conference on Informatics, Electronics & Vision (ICIEV) and 2019 3rd International Conference on Imaging, Vision & Pattern Recognition (icIVPR),
2019
DOI:10.1109/ICIEV.2019.8858541
|
|
|
[183]
|
Proceedings of 2018 Chinese Intelligent Systems Conference
Lecture Notes in Electrical Engineering,
2019
DOI:10.1007/978-981-13-2291-4_16
|
|
|
[184]
|
Deep Semantic Segmentation of Kidney and Space-Occupying Lesion Area Based on SCNN and ResNet Models Combined with SIFT-Flow Algorithm
Journal of Medical Systems,
2019
DOI:10.1007/s10916-018-1116-1
|
|
|
[185]
|
Artificial intelligence in medical imaging of the liver
World Journal of Gastroenterology,
2019
DOI:10.3748/wjg.v25.i6.672
|
|
|
[186]
|
Radiological images and machine learning: Trends, perspectives, and prospects
Computers in Biology and Medicine,
2019
DOI:10.1016/j.compbiomed.2019.02.017
|
|
|
[187]
|
Deep Learning for Automated Segmentation of Liver Lesions at CT in Patients with Colorectal Cancer Liver Metastases
Radiology: Artificial Intelligence,
2019
DOI:10.1148/ryai.2019180014
|
|
|
[188]
|
The present and future of deep learning in radiology
European Journal of Radiology,
2019
DOI:10.1016/j.ejrad.2019.02.038
|
|
|
[189]
|
10th International Conference on Robotics, Vision, Signal Processing and Power Applications
Lecture Notes in Electrical Engineering,
2019
DOI:10.1007/978-981-13-6447-1_77
|
|
|
[190]
|
Deep Learning for Variational Multimodality Tumor Segmentation in PET/CT
Neurocomputing,
2019
DOI:10.1016/j.neucom.2018.10.099
|
|
|
[191]
|
6th International Conference on Advancements of Medicine and Health Care through Technology; 17–20 October 2018, Cluj-Napoca, Romania
IFMBE Proceedings,
2019
DOI:10.1007/978-981-13-6207-1_27
|
|
|
[192]
|
Automatic liver tumour segmentation in CT combining FCN and NMF-based deformable model
Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization,
2019
DOI:10.1080/21681163.2018.1493618
|
|
|
[193]
|
Detection of Liver Cancer Using Modified Fuzzy Clustering and Decision Tree Classifier in CT Images
Pattern Recognition and Image Analysis,
2019
DOI:10.1134/S1054661819020056
|
|
|
[194]
|
A Systematic Survey of Computer-Aided Diagnosis in Medicine: Past and Present Developments
Expert Systems with Applications,
2019
DOI:10.1016/j.eswa.2019.112821
|
|
|
[195]
|
Liver Tumor Segmentation Based on Multi-Scale Candidate Generation and Fractal Residual Network
IEEE Access,
2019
DOI:10.1109/ACCESS.2019.2923218
|
|
|
[196]
|
Hyper‐reflective foci segmentation in SD‐OCT retinal images with diabetic retinopathy using deep convolutional neural networks
Medical Physics,
2019
DOI:10.1002/mp.13728
|
|
|
[197]
|
Cancer Diagnosis Using Deep Learning: A Bibliographic Review
Cancers,
2019
DOI:10.3390/cancers11091235
|
|
|
[198]
|
VipIMAGE 2019
Lecture Notes in Computational Vision and Biomechanics,
2019
DOI:10.1007/978-3-030-32040-9_30
|
|
|
[199]
|
A review of medical image detection for cancers in digestive system based on artificial intelligence
Expert Review of Medical Devices,
2019
DOI:10.1080/17434440.2019.1669447
|
|
|
[200]
|
Medical Image Computing and Computer Assisted Intervention – MICCAI 2019
Lecture Notes in Computer Science,
2019
DOI:10.1007/978-3-030-32245-8_27
|
|
|
[201]
|
HCC Recognition Within Ultrasound Images Employing Advanced Textural Features with Deep Learning Techniques
2019 12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI),
2019
DOI:10.1109/CISP-BMEI48845.2019.8965874
|
|
|
[202]
|
CU-Net: Cascaded U-Net Model for Automated Liver and Lesion Segmentation and Summarization
2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM),
2019
DOI:10.1109/BIBM47256.2019.8983266
|
|
|
[203]
|
Brain Tissue Segmentation Integrating Multi-level Features
2019 Seventh International Conference on Advanced Cloud and Big Data (CBD),
2019
DOI:10.1109/CBD.2019.00050
|
|
|
[204]
|
A modified scheme for liver tumor segmentation based on cascaded FCNs
Proceedings of the International Conference on Artificial Intelligence, Information Processing and Cloud Computing - AIIPCC '19,
2019
DOI:10.1145/3371425.3371451
|
|
|
[205]
|
Automatic Detection of Focal Liver Lesions in Multi-phase CT Images Using A Multi-channel & Multi-scale CNN
2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC),
2019
DOI:10.1109/EMBC.2019.8857292
|
|
|
[206]
|
Liver Detection Algorithm Based on an Improved Deep Network Combined With Edge Perception
IEEE Access,
2019
DOI:10.1109/ACCESS.2019.2953517
|
|
|
[207]
|
Assessment of the response of hepatocellular carcinoma to interventional radiology treatments
Future Oncology,
2019
DOI:10.2217/fon-2018-0747
|
|
|
[208]
|
Analysis of Parkinson’s Disease Data
Procedia Computer Science,
2018
DOI:10.1016/j.procs.2018.10.306
|
|
|
[209]
|
Automatic Tumor Segmentation Using Machine Learning Classifiers
2018 IEEE International Conference on Electro/Information Technology (EIT),
2018
DOI:10.1109/EIT.2018.8500205
|
|
|
[210]
|
Deep learning in medical imaging and radiation therapy
Medical Physics,
2018
DOI:10.1002/mp.13264
|
|
|
[211]
|
Computer-assisted frameworks for classification of liver, breast and blood neoplasias via neural networks: A survey based on medical images
Neurocomputing,
2018
DOI:10.1016/j.neucom.2018.06.080
|
|
|
[212]
|
Deep learning based liver cancer detection using watershed transform and Gaussian mixture model techniques
Cognitive Systems Research,
2018
DOI:10.1016/j.cogsys.2018.12.009
|
|
|
[213]
|
Texture-specific bag of visual words model and spatial cone matching-based method for the retrieval of focal liver lesions using multiphase contrast-enhanced CT images
International Journal of Computer Assisted Radiology and Surgery,
2018
DOI:10.1007/s11548-017-1671-9
|
|
|
[214]
|
Fully convolutional network and sparsity-based dictionary learning for liver lesion detection in CT examinations
Neurocomputing,
2018
DOI:10.1016/j.neucom.2017.10.001
|
|
|
[215]
|
Patient-specific and global convolutional neural networks for robust automatic liver tumor delineation in follow-up CT studies
Medical & Biological Engineering & Computing,
2018
DOI:10.1007/s11517-018-1803-6
|
|
|
[216]
|
Computer aided detection of ureteral stones in thin slice computed tomography volumes using Convolutional Neural Networks
Computers in Biology and Medicine,
2018
DOI:10.1016/j.compbiomed.2018.04.021
|
|
|
[217]
|
Deep learning for image-based cancer detection and diagnosis − A survey
Pattern Recognition,
2018
DOI:10.1016/j.patcog.2018.05.014
|
|
|
[218]
|
Comparison of regularization techniques for DCNN-based abdominal aortic aneurysm segmentation
2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018),
2018
DOI:10.1109/ISBI.2018.8363708
|
|
|
[219]
|
Intelligent Computing Methodologies
Lecture Notes in Computer Science,
2018
DOI:10.1007/978-3-319-95957-3_26
|
|
|
[220]
|
A Unified Level Set Framework Combining Hybrid Algorithms for Liver and Liver Tumor Segmentation in CT Images
BioMed Research International,
2018
DOI:10.1155/2018/3815346
|
|
|
[221]
|
Patch-Based Techniques in Medical Imaging
Lecture Notes in Computer Science,
2018
DOI:10.1007/978-3-030-00500-9_7
|
|
|
[222]
|
Renal Segmentation Algorithm Combined Low-level Features with Deep Coding Feature
2018 27th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN),
2018
DOI:10.1109/ROMAN.2018.8525519
|
|
|
[223]
|
Traffic sign integrity analysis using deep learning
2018 IEEE 14th International Colloquium on Signal Processing & Its Applications (CSPA),
2018
DOI:10.1109/CSPA.2018.8368695
|
|
|
[224]
|
Learning normalized inputs for iterative estimation in medical image segmentation
Medical Image Analysis,
2018
DOI:10.1016/j.media.2017.11.005
|
|
|
[225]
|
Patch-Based Techniques in Medical Imaging
Lecture Notes in Computer Science,
2018
DOI:10.1007/978-3-030-00500-9_7
|
|
|
[226]
|
Automatic segmentation of liver tumors from multiphase contrast-enhanced CT images based on FCNs
Artificial Intelligence in Medicine,
2017
DOI:10.1016/j.artmed.2017.03.008
|
|
|
[227]
|
3D-Brain Segmentation Using Deep Neural Network and Gaussian Mixture Model
2017 IEEE Winter Conference on Applications of Computer Vision (WACV),
2017
DOI:10.1109/WACV.2017.96
|
|
|
[228]
|
A survey on deep learning in medical image analysis
Medical Image Analysis,
2017
DOI:10.1016/j.media.2017.07.005
|
|
|
[229]
|
Automatic detection of new tumors and tumor burden evaluation in longitudinal liver CT scan studies
International Journal of Computer Assisted Radiology and Surgery,
2017
DOI:10.1007/s11548-017-1660-z
|
|
|
[230]
|
Texture-based treatment prediction by automatic liver tumor segmentation on computed tomography
2017 International Conference on Computer, Information and Telecommunication Systems (CITS),
2017
DOI:10.1109/CITS.2017.8035318
|
|
|
[231]
|
3D Liver Tumor Segmentation in CT Images Using Improved Fuzzy C-Means and Graph Cuts
BioMed Research International,
2017
DOI:10.1155/2017/5207685
|
|
|
[232]
|
Liver lesion segmentation in CT images with MK-FCN
2017 IEEE 2nd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC),
2017
DOI:10.1109/IAEAC.2017.8054322
|
|
|
[233]
|
Classification of dental diseases using CNN and transfer learning
2017 5th International Symposium on Computational and Business Intelligence (ISCBI),
2017
DOI:10.1109/ISCBI.2017.8053547
|
|
|
[234]
|
Deep Learning and Data Labeling for Medical Applications
Lecture Notes in Computer Science,
2016
DOI:10.1007/978-3-319-46976-8_9
|
|
|