Skin Cancer Classification with Convolutional Deep Neural Networks and Vision Transformers Using Transfer Learning
The deadliest type of skin cancer is melanoma. Melanocytes are the cells where cancerous
growths take place. The cells create melanin pigment, which gives skin its color. Sun …
growths take place. The cells create melanin pigment, which gives skin its color. Sun …
A fine tuning approach using modified DenseNet model for skin cancer classification
A Mondal, VK Shrivastava - International Journal of Medical …, 2023 - inderscienceonline.com
Skin cancer is one of the deadliest types of all cancers and melanoma is the severest form of
it. In this paper, we have used three state-of-the-art deep convolutional neural network …
it. In this paper, we have used three state-of-the-art deep convolutional neural network …
Deep learning for skin lesion segmentation
Z MiriKharaji - 2022 - summit.sfu.ca
Skin cancer is a major public health problem requiring computer aided diagnosis to reduce
the burden of disease's high incidence ratio and the associated expenses by assisting …
the burden of disease's high incidence ratio and the associated expenses by assisting …
Invasive Ductal Carcinoma Detection by A Gated Recurrent Unit Network with Self Attention
Representing around 80% of breast cancer, Invasive Ductal Carcinoma is the most common
type of breast cancer. In this work, we have proposed a self-attention GRU model to detect …
type of breast cancer. In this work, we have proposed a self-attention GRU model to detect …
[PDF][PDF] Medical diagnostic support system based on breast thermography using Raspberry Pi and cloud computing
NK Chebbah, M Ouslim - Indonesian Journal of Electrical …, 2022 - academia.edu
Breast thermography is a promising medical imaging technique for the detection of breast
cancer. However, providing a robust and portable computer-aided diagnostic system for …
cancer. However, providing a robust and portable computer-aided diagnostic system for …
U-net based deep learning architectures for object segmentation in biomedical images
N Siddique - 2021 - search.proquest.com
U-net is an image segmentation technique developed primarily for medical image analysis
that can precisely segment images using a scarce amount of training data. These traits …
that can precisely segment images using a scarce amount of training data. These traits …
A Comparative Review of the Role of Deep Learning in Medical Image Processing
Nowadays, in the medical sector, Deep Learning methods act as a dynamic character in the
analysis of medical images and identification of diseases. The ease of understanding the …
analysis of medical images and identification of diseases. The ease of understanding the …
[PDF][PDF] Performance Evaluation of U-Net Based Methods for Lesion Segmentation from Dermoscopy Images
Skin cancer accounts for approximately half of all cancer cases worldwide, making it one of
the most prevalent types of cancer. Melanoma, which develops from melanocytes that give …
the most prevalent types of cancer. Melanoma, which develops from melanocytes that give …
Skin lesion segmentation using deep convolutional networks
Skin cancer is one of the most common forms of cancer causing millions of deaths around
the world. Recently, many advanced approaches are adopted to detect the lesion with the …
the world. Recently, many advanced approaches are adopted to detect the lesion with the …
Automatic classification of melanocytic skin tumors based on hyperparameters optimized by cross-validation using support vector machines
O Gokkan, S Tozburun - Photonics in Dermatology and Plastic …, 2020 - spiedigitallibrary.org
Melanocytic lesions may occur in various areas of the skin and may eventually develop into
malignant tissue types as a result of abnormal tissue growth. Although the gold standard for …
malignant tissue types as a result of abnormal tissue growth. Although the gold standard for …