Fine-grained classification of skin cancer types using deep neural networks on medical images

Nitish Kumar; Hidangmayum Bebina; Sudharsana Rao Potturu; Prakash Duraisamy; Tushar Sandhan

doi:10.1117/12.2664153

13 June 2023 Fine-grained classification of skin cancer types using deep neural networks on medical images

Nitish Kumar, Hidangmayum Bebina, Sudharsana Rao Potturu, Prakash Duraisamy, Tushar Sandhan

Proceedings Volume 12527, Pattern Recognition and Tracking XXXIV; 125270H (2023) https://doi.org/10.1117/12.2664153
Event: SPIE Defense + Commercial Sensing, 2023, Orlando, Florida, United States

Abstract

Cancer has a tremendous present impact on human existence due to its extremely high global death rate. Malignant melanoma of the skin accounts for 20 daily deaths in the United States. Malignant melanomas (MEL), basal cell carcinomas (BCC), actinic keratoses intraepithelial carcinomas (AKIEC), nevi (melanocytic), keratinocytic lesions (BKL), dermatofibromas (DF), and vascular lesions (VL) are the seven main types of skin cancer (VASC). It might be challenging to recognize and classify different cancer kinds frombiomedical imaging, as there are many sub-cancer types that differ significantly from one another. Several researchers and doctors are currently trying to pinpoint the most effective means of spotting skin cancer in its earliest stages. Using multiple residual and sequential convolutional neural networks,we present a learning strategy for cancer classification in this research. An effort is made here to more precisely categorize MEL, BCC, and BKL cancers. F1 score, precision, recall, and accuracy are used to verify the validity of the proposed model. Results show the reliability and validity of the model.

Conference Presentation

Citation Download Citation

Nitish Kumar, Hidangmayum Bebina, Sudharsana Rao Potturu, Prakash Duraisamy, and Tushar Sandhan "Fine-grained classification of skin cancer types using deep neural networks on medical images", Proc. SPIE 12527, Pattern Recognition and Tracking XXXIV, 125270H (13 June 2023); https://doi.org/10.1117/12.2664153

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