Melanoma Is Skin Deep: A 3D Reconstruction Technique for Computerized Dermoscopic Skin Lesion Classification
Melanoma mortality rates are the highest amongst skin cancer patients. Melanoma is life threating when it grows beyond the dermis of the skin. Hence, depth is an important factor to diagnose melanoma. This paper introduces a non-invasive computerized dermoscopy system that considers the estimated de...
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| Format: | Article |
| Language: | English |
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IEEE
2017-01-01
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| Series: | IEEE Journal of Translational Engineering in Health and Medicine |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/7819474/ |
| _version_ | 1818331654226182144 |
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| author | T. Y. Satheesha D. Satyanarayana M. N. Giri Prasad Kashyap D. Dhruve |
| author_facet | T. Y. Satheesha D. Satyanarayana M. N. Giri Prasad Kashyap D. Dhruve |
| author_sort | T. Y. Satheesha |
| collection | DOAJ |
| description | Melanoma mortality rates are the highest amongst skin cancer patients. Melanoma is life threating when it grows beyond the dermis of the skin. Hence, depth is an important factor to diagnose melanoma. This paper introduces a non-invasive computerized dermoscopy system that considers the estimated depth of skin lesions for diagnosis. A 3-D skin lesion reconstruction technique using the estimated depth obtained from regular dermoscopic images is presented. On basis of the 3-D reconstruction, depth and 3-D shape features are extracted. In addition to 3-D features, regular color, texture, and 2-D shape features are also extracted. Feature extraction is critical to achieve accurate results. Apart from melanoma, in-situ melanoma the proposed system is designed to diagnose basal cell carcinoma, blue nevus, dermatofibroma, haemangioma, seborrhoeic keratosis, and normal mole lesions. For experimental evaluations, the PH2, ISIC: Melanoma Project, and ATLAS dermoscopy data sets is considered. Different feature set combinations is considered and performance is evaluated. Significant performance improvement is reported the post inclusion of estimated depth and 3-D features. The good classification scores of sensitivity = 96%, specificity = 97% on PH2 data set and sensitivity = 98%, specificity = 99% on the ATLAS data set is achieved. Experiments conducted to estimate tumor depth from 3-D lesion reconstruction is presented. Experimental results achieved prove that the proposed computerized dermoscopy system is efficient and can be used to diagnose varied skin lesion dermoscopy images. |
| first_indexed | 2024-12-13T13:23:17Z |
| format | Article |
| id | doaj.art-cb8665b641b44aa4b79ccb9433cb3d62 |
| institution | Directory Open Access Journal |
| issn | 2168-2372 |
| language | English |
| last_indexed | 2024-12-13T13:23:17Z |
| publishDate | 2017-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Journal of Translational Engineering in Health and Medicine |
| spelling | doaj.art-cb8665b641b44aa4b79ccb9433cb3d622022-12-21T23:44:21ZengIEEEIEEE Journal of Translational Engineering in Health and Medicine2168-23722017-01-01511710.1109/JTEHM.2017.26487977819474Melanoma Is Skin Deep: A 3D Reconstruction Technique for Computerized Dermoscopic Skin Lesion ClassificationT. Y. Satheesha0D. Satyanarayana1M. N. Giri Prasad2Kashyap D. Dhruve3Electronics and Communication Engineering Department, Nagarjuna College of Engineering and Technology, Bengaluru, IndiaElectronics and Communication Engineering Department, Rajeev Gandhi Memorial College of Engineering and Technology, Nandyala, IndiaElectronics and Communication Engineering Department, Jawaharlal Nehru Technological University Anantapur, Anantapur, IndiaResearch and Development Team, Planet-I Technologies, Bengaluru, IndiaMelanoma mortality rates are the highest amongst skin cancer patients. Melanoma is life threating when it grows beyond the dermis of the skin. Hence, depth is an important factor to diagnose melanoma. This paper introduces a non-invasive computerized dermoscopy system that considers the estimated depth of skin lesions for diagnosis. A 3-D skin lesion reconstruction technique using the estimated depth obtained from regular dermoscopic images is presented. On basis of the 3-D reconstruction, depth and 3-D shape features are extracted. In addition to 3-D features, regular color, texture, and 2-D shape features are also extracted. Feature extraction is critical to achieve accurate results. Apart from melanoma, in-situ melanoma the proposed system is designed to diagnose basal cell carcinoma, blue nevus, dermatofibroma, haemangioma, seborrhoeic keratosis, and normal mole lesions. For experimental evaluations, the PH2, ISIC: Melanoma Project, and ATLAS dermoscopy data sets is considered. Different feature set combinations is considered and performance is evaluated. Significant performance improvement is reported the post inclusion of estimated depth and 3-D features. The good classification scores of sensitivity = 96%, specificity = 97% on PH2 data set and sensitivity = 98%, specificity = 99% on the ATLAS data set is achieved. Experiments conducted to estimate tumor depth from 3-D lesion reconstruction is presented. Experimental results achieved prove that the proposed computerized dermoscopy system is efficient and can be used to diagnose varied skin lesion dermoscopy images.https://ieeexplore.ieee.org/document/7819474/Melanoma in-situskin lesionsclassification3D lesion reconstruction3D features and tumor depth estimation |
| spellingShingle | T. Y. Satheesha D. Satyanarayana M. N. Giri Prasad Kashyap D. Dhruve Melanoma Is Skin Deep: A 3D Reconstruction Technique for Computerized Dermoscopic Skin Lesion Classification IEEE Journal of Translational Engineering in Health and Medicine Melanoma in-situ skin lesions classification 3D lesion reconstruction 3D features and tumor depth estimation |
| title | Melanoma Is Skin Deep: A 3D Reconstruction Technique for Computerized Dermoscopic Skin Lesion Classification |
| title_full | Melanoma Is Skin Deep: A 3D Reconstruction Technique for Computerized Dermoscopic Skin Lesion Classification |
| title_fullStr | Melanoma Is Skin Deep: A 3D Reconstruction Technique for Computerized Dermoscopic Skin Lesion Classification |
| title_full_unstemmed | Melanoma Is Skin Deep: A 3D Reconstruction Technique for Computerized Dermoscopic Skin Lesion Classification |
| title_short | Melanoma Is Skin Deep: A 3D Reconstruction Technique for Computerized Dermoscopic Skin Lesion Classification |
| title_sort | melanoma is skin deep a 3d reconstruction technique for computerized dermoscopic skin lesion classification |
| topic | Melanoma in-situ skin lesions classification 3D lesion reconstruction 3D features and tumor depth estimation |
| url | https://ieeexplore.ieee.org/document/7819474/ |
| work_keys_str_mv | AT tysatheesha melanomaisskindeepa3dreconstructiontechniqueforcomputerizeddermoscopicskinlesionclassification AT dsatyanarayana melanomaisskindeepa3dreconstructiontechniqueforcomputerizeddermoscopicskinlesionclassification AT mngiriprasad melanomaisskindeepa3dreconstructiontechniqueforcomputerizeddermoscopicskinlesionclassification AT kashyapddhruve melanomaisskindeepa3dreconstructiontechniqueforcomputerizeddermoscopicskinlesionclassification |