Fuzzy C Mean Thresholding based Level Set for Automated Segmentation of Skin Lesions

Journals Menu

Follow SCIRP

	customer@scirp.org
	+86 18163351462(WhatsApp)
	1655362766

	Paper Publishing WeChat

Journal of Signal and Information Processing

ISSN Print: 2159-4465
ISSN Online: 2159-4481
www.scirp.org/journal/jsip
E-mail: jsip@scirp.org

Google-based Impact Factor: 1.78
Citations

Journals Menu

"Fuzzy C Mean Thresholding based Level Set for Automated Segmentation of Skin Lesions"
written by Ammara Masood, Adel Ali Al-Jumaily,
published by Journal of Signal and Information Processing, Vol.4 No.3B, 2013

has been cited by the following article(s):

Google Scholar
CrossRef

[1]	Fuzzy Thresholding-Based Brain Image Segmentation Using Multi-Threshold Level Set Model
	Driving Smart Medical Diagnosis …, 2024

[2]	An Automatic Early Detection
	Smart Trends in Computing and …, 2023

[3]	An Automatic Early Detection of Melanoma Skin Cancer Using Fuzzy C-Means
	International Conference on Smart Trends …, 2023

[4]	Di-unet: dual-branch interactive u-net for skin cancer image segmentation
	Journal of Cancer Research and Clinical Oncology, 2023

[5]	Image segmentation of skin lesions based on dense atrous spatial pyramid pooling and attention mechanism
	Sheng wu yi xue Gong Cheng …, 2022

[6]	Nitrogen Deficiency and Yield Estimation in Paddy Field
	… Conference on DATA ANALYTICS & LEARNING, 2022

[7]	基于密集空洞空间金字塔池化和注意力机制的皮肤病灶图像分割方法
	… Wu Yi Xue Gong Cheng Xue …, 2022

[8]	The Fast and Accurate Approach to Detection and Segmentation of Melanoma Skin Cancer using Fine-tuned Yolov3 and SegNet Based on Deep Transfer Learning
	arXiv preprint arXiv:2210.05167, 2022

[9]	A comparative analysis of melanoma detection methods based on computer aided diagnose system
	Materials Today: Proceedings, 2022

[10]	Deep Learning-Based Melanoma Detection with Optimized Features via Hybrid Algorithm
	International Journal of Image and Graphics, 2022

[11]	Image Processing and Analysis for Decision Making Applied to Melanoma
	Advanced Methods for Human Biometrics, 2021

[12]	A Segmentation of Melanocytic Skin Lesions in Dermoscopic and Standard Images Using a Hybrid Two-Stage Approach
	2021

[13]	A brain extraction algorithm for infant T2 weighted magnetic resonance images based on fuzzy c-means thresholding
	Scientific Reports, 2021

[14]	MATLAB image processing tool-based GUI for high-throughput image segmentation and analysis to study structure and morphology of skin H&E stained sections
	2020

[15]	Directional Vector-Based Skin Lesion Segmentation—A Novel Approach to Skin Segmentation
	2020

[16]	Melanoma lesion detection and segmentation using YOLOv4-DarkNet and active contour
	2020

[17]	Engineering and Technology for Healthcare
	2020

[18]	Automated Diagnosis of Skin Cancer for Healthcare: Highlights and Procedures
	2020

[19]	A Comparative Study of Meningioma Tumors Segmentation Methods from MR Images
	2020

[20]	Construction of saliency map and hybrid set of features for efficient segmentation and classification of skin lesion
	2019

[21]	Detection and diagnosis of dilated cardiomyopathy from the left ventricular parameters in echocardiogram sequences
	2019

[22]	Supervised Saliency Map Driven Segmentation of Lesions in Dermoscopic Images
	2018

[23]	New FCM Segmentation Approach Based on Multi-Resolution Analysis
	International Journal of Fuzzy System Applications (IJFSA), 2018

[24]	Segmentation of Melanoma Skin Lesions Using Anisotropic Diffusion and Adaptive Thresholding
	ICBET 2018 Proceedings of the 2018 8th International Conference on Biomedical Engineering and Technology, 2018

[25]	Detection of Fonts and Characters with Hybrid Graphic-Text Plate Numbers
	2018

[26]	Orientation Sensitive Fuzzy C Means Based Fast Level Set Evolution for Segmentation of Histopathological Images to Detect Skin Cancer
	2018

[27]	Implementation of Fuzzy Thresholding for Segmentation of Images
	International Journal of Computer Applications, 2017

[28]	Αυτόματη Ανίχνευση Αθηρωματικής Πλάκας Σε Εικόνες B-Mode Υπερήχων Μέσω Ανάλυσης Υφής
	2017

[29]	Segmentation of Brain Tumour Based on Clustering Technique: Performance Analysis
	Journal of Intelligent Systems, 2017

[30]	Supervised Saliency Map Driven Segmentation of the Lesions in Dermoscopic Images
	IEEE JBHI; Special Issue on “Skin Lesion Image Analysis for Melanoma Detection” , 2017

[31]	Detection and diagnosis of dilated cardiomyopathy and hypertrophic cardiomyopathy using image processing techniques
	Engineering Science and Technology, an International Journal, 2016

[32]	Proposed Threshold Algorithm for Accurate Segmentation for Skin Lesion
	2016

[33]	Estudo comparativo de técnicas para segmentação e classificação de imagens de lesões de pele
	Repositório Institucional UNESP, 2016

[34]	Developing improved algorithms for detection and analysis of skin cancer
	2016

[35]	Enhancement of dermoscopic images and feature extraction for classification of skin lesions
	ProQuest Dissertations Publishing, 2015

[36]	GMM guided automated Level Set algorithm for PET image segmentation
	World Congress on Medical Physics and Biomedical Engineering, June 7-12, 2015, Toronto, Canada, 2015

[37]	Self-supervised learning model for skin cancer diagnosis
	2015 7th International IEEE/EMBS Conference on Neural Engineering (NER), 2015

[38]	A local fuzzy thresholding methodology for multiregion image segmentation
	Knowledge-Based Systems, 2015

[39]	SA-SVM based automated diagnostic system for skin cancer
	Sixth International Conference on Graphic and Image Processing (ICGIP 2014), 2015

[40]	Automatic skin cancer detection system
	2014

[41]	Texture Analysis Based Automated Decision Support System for Classification of Skin Cancer Using SA-SVM
	Neural Information Processing.Springer, 2014

[42]	Integrating soft and hard threshold selection algorithms for accurate segmentation of skin lesion
	Biomedical Engineering (MECBME), 2014 Middle East Conference on. IEEE, 2014

[43]	Development of Automated Diagnostic System for Skin Cancer: Performance Analysis of Neural Network Learning Algorithms for Classification
	Artificial Neural Networks and Machine Learning–ICANN 2014. Springer International Publishing, 2014

[44]	A BINARY LEVEL SET METHOD BASED ON K-MEANS FOR CONTOUR TRACKING ON SKIN CANCER IMAGES
	Proceeding (818) Biomedical Engineering / 817: Robotics Applications, 2014

[45]	A Hybrid Dermoscopic Images Segmentation Scheme Using Fast FCM, DWT2 and YUV
	IJEIR, 2014

[46]	A Hybrid Dermoscopic Images Segmentation Scheme Using Fast FCM DWT2 and YUV
	2014

[47]	Automated segmentation of skin lesions: Modified Fuzzy C mean thresholding based level set method
	Multi Topic Conference (INMIC), 2013 16th International. IEEE, 2013

[48]	Computer aided diagnostic support system for skin cancer: A review of techniques and algorithms
	International journal of biomedical imaging, 2013

[49]	Bilingual Visual Script Proof Based on Pre-trained Clustering and Neural Network

[1]	Driving Smart Medical Diagnosis Through AI-Powered Technologies and Applications Advances in Medical Diagnosis, Treatment, and Care, 2024 DOI:10.4018/979-8-3693-3679-3.ch007

[2]	Driving Smart Medical Diagnosis Through AI-Powered Technologies and Applications Advances in Medical Diagnosis, Treatment, and Care, 2024 DOI:10.4018/979-8-3693-3679-3.ch007

[3]	Smart Trends in Computing and Communications Lecture Notes in Networks and Systems, 2023 DOI:10.1007/978-981-99-0838-7_9

[4]	Smart Trends in Computing and Communications Lecture Notes in Networks and Systems, 2023 DOI:10.1007/978-981-99-0838-7_9

[5]	DI-UNet: dual-branch interactive U-Net for skin cancer image segmentation Journal of Cancer Research and Clinical Oncology, 2023 DOI:10.1007/s00432-023-05319-4

[6]	Deep Learning-Based Melanoma Detection with Optimized Features via Hybrid Algorithm International Journal of Image and Graphics, 2023 DOI:10.1142/S0219467823500560

[7]	Smart Trends in Computing and Communications Lecture Notes in Networks and Systems, 2023 DOI:10.1007/978-981-99-0838-7_9

[8]	Smart Trends in Computing and Communications Lecture Notes in Networks and Systems, 2023 DOI:10.1007/978-981-99-0838-7_9

[9]	Engineering and Technology for Healthcare 2021 DOI:10.1002/9781119644316.ch10

[10]	Engineering and Technology for Healthcare 2021 DOI:10.1002/9781119644316.ch10

[11]	A Segmentation of Melanocytic Skin Lesions in Dermoscopic and Standard Images Using a Hybrid Two‐Stage Approach BioMed Research International, 2021 DOI:10.1155/2021/5562801

[12]	A Segmentation of Melanocytic Skin Lesions in Dermoscopic and Standard Images Using a Hybrid Two-Stage Approach BioMed Research International, 2021 DOI:10.1155/2021/5562801

[13]	Advanced Methods for Human Biometrics Smart Sensors, Measurement and Instrumentation, 2021 DOI:10.1007/978-3-030-81982-8_12

[14]	MATLAB image processing tool-based GUI for high-throughput image segmentation and analysis to study structure and morphology of skin H&E stained sections IOP Conference Series: Materials Science and Engineering, 2020 DOI:10.1088/1757-899X/737/1/012232

[15]	A Comparative Study of Meningioma Tumors Segmentation Methods from MR Images 2020 3rd International Conference on Signal Processing and Information Security (ICSPIS), 2020 DOI:10.1109/ICSPIS51252.2020.9340134

[16]	Directional Vector-Based Skin Lesion Segmentation — A Novel Approach to Skin Segmentation International Journal of Image and Graphics, 2020 DOI:10.1142/S0219467820500217

[17]	Melanoma Lesion Detection and Segmentation Using YOLOv4-DarkNet and Active Contour IEEE Access, 2020 DOI:10.1109/ACCESS.2020.3035345

[18]	Construction of saliency map and hybrid set of features for efficient segmentation and classification of skin lesion Microscopy Research and Technique, 2019 DOI:10.1002/jemt.23220

[19]	Construction of saliency map and hybrid set of features for efficient segmentation and classification of skin lesion Microscopy Research and Technique, 2019 DOI:10.1002/jemt.23220

[20]	Detection of Fonts and Characters with Hybrid Graphic-Text Plate Numbers TENCON 2018 - 2018 IEEE Region 10 Conference, 2018 DOI:10.1109/TENCON.2018.8650097

[21]	New FCM Segmentation Approach Based on Multi-Resolution Analysis International Journal of Fuzzy System Applications, 2018 DOI:10.4018/IJFSA.2018100105

[22]	Segmentation of Melanoma Skin Lesions Using Anisotropic Diffusion and Adaptive Thresholding Proceedings of the 2018 8th International Conference on Biomedical Engineering and Technology, 2018 DOI:10.1145/3208955.3208961

[23]	Segmentation of Melanoma Skin Lesions Using Anisotropic Diffusion and Adaptive Thresholding Proceedings of the 2018 8th International Conference on Biomedical Engineering and Technology - ICBET '18, 2018 DOI:10.1145/3208955.3208961

[24]	Oncology 2017 DOI:10.4018/978-1-5225-0549-5.ch009

[25]	Segmentation of Brain Tumour Based on Clustering Technique: Performance Analysis Journal of Intelligent Systems, 2017 DOI:10.1515/jisys-2017-0027

[26]	SA-SVM based automated diagnostic system for skin cancer Sixth International Conference on Graphic and Image Processing (ICGIP 2014), 2015 DOI:10.1117/12.2179094

[27]	A local fuzzy thresholding methodology for multiregion image segmentation Knowledge-Based Systems, 2015 DOI:10.1016/j.knosys.2015.02.029

[28]	Self-supervised learning model for skin cancer diagnosis 2015 7th International IEEE/EMBS Conference on Neural Engineering (NER), 2015 DOI:10.1109/NER.2015.7146798

[29]	Integrating soft and hard threshold selection algorithms for accurate segmentation of skin lesion 2nd Middle East Conference on Biomedical Engineering, 2014 DOI:10.1109/MECBME.2014.6783212

[30]	Neural Information Processing Lecture Notes in Computer Science, 2014 DOI:10.1007/978-3-319-12640-1_13

[31]	Artificial Neural Networks and Machine Learning – ICANN 2014 Lecture Notes in Computer Science, 2014 DOI:10.1007/978-3-319-11179-7_105

[32]	Computer Aided Diagnostic Support System for Skin Cancer: A Review of Techniques and Algorithms International Journal of Biomedical Imaging, 2013 DOI:10.1155/2013/323268

[33]	Automated segmentation of skin lesions: Modified Fuzzy C mean thresholding based level set method INMIC, 2013 DOI:10.1109/INMIC.2013.6731350

Follow SCIRP

	customer@scirp.org
	+86 18163351462(WhatsApp)
	1655362766

	Paper Publishing WeChat

Journal of Signal and Information Processing

Journal of Signal and Information Processing

Journals Menu

Home

About SCIRP

Service

Policies