Literature DB >> 24110966

PH² - a dermoscopic image database for research and benchmarking.

Teresa Mendonca, Pedro M Ferreira, Jorge S Marques, Andre R S Marcal, Jorge Rozeira.   

Abstract

The increasing incidence of melanoma has recently promoted the development of computer-aided diagnosis systems for the classification of dermoscopic images. Unfortunately, the performance of such systems cannot be compared since they are evaluated in different sets of images by their authors and there are no public databases available to perform a fair evaluation of multiple systems. In this paper, a dermoscopic image database, called PH², is presented. The PH² database includes the manual segmentation, the clinical diagnosis, and the identification of several dermoscopic structures, performed by expert dermatologists, in a set of 200 dermoscopic images. The PH² database will be made freely available for research and benchmarking purposes.

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Year:  2013        PMID: 24110966     DOI: 10.1109/EMBC.2013.6610779

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  46 in total

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Journal:  Med Biol Eng Comput       Date:  2018-05-15       Impact factor: 2.602

3.  An Efficient Melanoma Diagnosis Approach Using Integrated HMF Multi-Atlas Map Based Segmentation.

Authors:  D Roja Ramani; S Siva Ranjani
Journal:  J Med Syst       Date:  2019-06-12       Impact factor: 4.460

4.  Skin Lesion Segmentation with Improved Convolutional Neural Network.

Authors:  Şaban Öztürk; Umut Özkaya
Journal:  J Digit Imaging       Date:  2020-08       Impact factor: 4.056

5.  Novel Approaches for Diagnosing Melanoma Skin Lesions Through Supervised and Deep Learning Algorithms.

Authors:  J Premaladha; K S Ravichandran
Journal:  J Med Syst       Date:  2016-02-12       Impact factor: 4.460

6.  Melanoma Is Skin Deep: A 3D Reconstruction Technique for Computerized Dermoscopic Skin Lesion Classification.

Authors:  T Y Satheesha; D Satyanarayana; M N Giri Prasad; Kashyap D Dhruve
Journal:  IEEE J Transl Eng Health Med       Date:  2017-01-16       Impact factor: 3.316

7.  Hybrid two-stage active contour method with region and edge information for intensity inhomogeneous image segmentation.

Authors:  Shafiullah Soomro; Asad Munir; Kwang Nam Choi
Journal:  PLoS One       Date:  2018-01-29       Impact factor: 3.240

8.  Detection of Malignant Melanoma Using Artificial Intelligence: An Observational Study of Diagnostic Accuracy.

Authors:  Michael Phillips; Jack Greenhalgh; Helen Marsden; Ioulios Palamaras
Journal:  Dermatol Pract Concept       Date:  2019-12-31

9.  Noninvasive Real-Time Automated Skin Lesion Analysis System for Melanoma Early Detection and Prevention.

Authors:  Omar Abuzaghleh; Buket D Barkana; Miad Faezipour
Journal:  IEEE J Transl Eng Health Med       Date:  2015-04-03       Impact factor: 3.316

Review 10.  Skin Cancer Detection: A Review Using Deep Learning Techniques.

Authors:  Mehwish Dildar; Shumaila Akram; Muhammad Irfan; Hikmat Ullah Khan; Muhammad Ramzan; Abdur Rehman Mahmood; Soliman Ayed Alsaiari; Abdul Hakeem M Saeed; Mohammed Olaythah Alraddadi; Mater Hussen Mahnashi
Journal:  Int J Environ Res Public Health       Date:  2021-05-20       Impact factor: 3.390

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