Literature DB >> 20832242

Gradient vector flow with mean shift for skin lesion segmentation.

Huiyu Zhou1, Gerald Schaefer, M Emre Celebi, Faquan Lin, Tangwei Liu.   

Abstract

Image segmentation is an important task in the analysis of dermoscopy images since the extraction of skin lesion borders provides important cues for accurate diagnosis. In recent years, gradient vector flow based algorithms have demonstrated their merits in image segmentation. However, due to the compromise of internal and external energy forces within the partial differential equation these methods commonly lead to under- or over-segmentation problems. In this paper, we introduce a new mean shift based gradient vector flow (GVF) algorithm that drives the internal/external energies towards the correct direction. The proposed segmentation method incorporates a mean shift operation within the standard GVF cost function. Theoretical analysis proves that the proposed algorithm converges rapidly, while experimental results on a large set of diverse dermoscopy images demonstrate that the presented method accurately determines skin lesion borders in dermoscopy images.
Copyright © 2010 Elsevier Ltd. All rights reserved.

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Year:  2010        PMID: 20832242     DOI: 10.1016/j.compmedimag.2010.08.002

Source DB:  PubMed          Journal:  Comput Med Imaging Graph        ISSN: 0895-6111            Impact factor:   4.790


  10 in total

1.  Modified watershed technique and post-processing for segmentation of skin lesions in dermoscopy images.

Authors:  Hanzheng Wang; Randy H Moss; Xiaohe Chen; R Joe Stanley; William V Stoecker; M Emre Celebi; Joseph M Malters; James M Grichnik; Ashfaq A Marghoob; Harold S Rabinovitz; Scott W Menzies; Thomas M Szalapski
Journal:  Comput Med Imaging Graph       Date:  2010-10-20       Impact factor: 4.790

2.  Hair detection and lesion segmentation in dermoscopic images using domain knowledge.

Authors:  Sameena Pathan; K Gopalakrishna Prabhu; P C Siddalingaswamy
Journal:  Med Biol Eng Comput       Date:  2018-05-15       Impact factor: 2.602

3.  Developing a Recognition System for Diagnosing Melanoma Skin Lesions Using Artificial Intelligence Algorithms.

Authors:  Fawaz Waselallah Alsaade; Theyazn H H Aldhyani; Mosleh Hmoud Al-Adhaileh
Journal:  Comput Math Methods Med       Date:  2021-05-15       Impact factor: 2.238

4.  Automatic lesion border selection in dermoscopy images using morphology and color features.

Authors:  Nabin K Mishra; Ravneet Kaur; Reda Kasmi; Jason R Hagerty; Robert LeAnder; Ronald J Stanley; Randy H Moss; William V Stoecker
Journal:  Skin Res Technol       Date:  2019-03-14       Impact factor: 2.365

5.  NeDSeM: Neutrosophy Domain-Based Segmentation Method for Malignant Melanoma Images.

Authors:  Xiaofei Bian; Haiwei Pan; Kejia Zhang; Chunling Chen; Peng Liu; Kun Shi
Journal:  Entropy (Basel)       Date:  2022-06-02       Impact factor: 2.738

6.  Adaptive bacteria colony picking in unstructured environments using intensity histogram and unascertained LS-SVM classifier.

Authors:  Kun Zhang; Minrui Fei; Xin Li; Huiyu Zhou
Journal:  ScientificWorldJournal       Date:  2014-05-12

7.  Skin Lesion Analysis towards Melanoma Detection Using Deep Learning Network.

Authors:  Yuexiang Li; Linlin Shen
Journal:  Sensors (Basel)       Date:  2018-02-11       Impact factor: 3.576

8.  A New Algorithm for Skin Lesion Border Detection in Dermoscopy Images.

Authors:  E Meskini; M S Helfroush; K Kazemi; M Sepaskhah
Journal:  J Biomed Phys Eng       Date:  2018-03-01

9.  Application of automatic statistical post-processing method for analysis of ultrasonic and digital dermatoscopy images.

Authors:  Indre Drulyte; Tomas Ruzgas; Renaldas Raisutis; Skaidra Valiukeviciene; Gintare Linkeviciute
Journal:  Libyan J Med       Date:  2018-12       Impact factor: 1.657

10.  Employing the Local Radon Transform for Melanoma Segmentation in Dermoscopic Images.

Authors:  Alireza Amoabedini; Mahsa Saffari Farsani; Hamidreza Saberkari; Ehsan Aminian
Journal:  J Med Signals Sens       Date:  2018 Jul-Sep
  10 in total

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