AI-powered diagnosis of skin cancer: a contemporary review, open challenges and future research directions

N Melarkode, K Srinivasan, SM Qaisar, P Plawiak - Cancers, 2023 - mdpi.com
Simple Summary The proposed research aims to provide a deep insight into the deep
learning and machine learning techniques used for diagnosing skin cancer. While …

Breast tumor localization and segmentation using machine learning techniques: Overview of datasets, findings, and methods

R Ranjbarzadeh, S Dorosti, SJ Ghoushchi… - Computers in Biology …, 2023 - Elsevier
Abstract The Global Cancer Statistics 2020 reported breast cancer (BC) as the most
common diagnosis of cancer type. Therefore, early detection of such type of cancer would …

IoMT cloud-based intelligent prediction of breast cancer stages empowered with deep learning

SY Siddiqui, A Haider, TM Ghazal, MA Khan… - IEEE …, 2021 - ieeexplore.ieee.org
Breast cancer is often a fatal disease that has a substantial impact on the female mortality
rate. Rapidly spreading breast cancer is due to the abnormal growth of malignant cells in the …

Multiple skin lesions diagnostics via integrated deep convolutional networks for segmentation and classification

MA Al-Masni, DH Kim, TS Kim - Computer methods and programs in …, 2020 - Elsevier
Background and objective Computer automated diagnosis of various skin lesions through
medical dermoscopy images remains a challenging task. Methods In this work, we propose …

Skin lesion segmentation in dermoscopy images via deep full resolution convolutional networks

MA Al-Masni, MA Al-Antari, MT Choi, SM Han… - Computer methods and …, 2018 - Elsevier
Background and objective Automatic segmentation of skin lesions in dermoscopy images is
still a challenging task due to the large shape variations and indistinct boundaries of the …

Evaluation of deep learning detection and classification towards computer-aided diagnosis of breast lesions in digital X-ray mammograms

MA Al-Antari, SM Han, TS Kim - Computer methods and programs in …, 2020 - Elsevier
Abstract Background and Objective Deep learning detection and classification from medical
imagery are key components for computer-aided diagnosis (CAD) systems to efficiently …

A fully integrated computer-aided diagnosis system for digital X-ray mammograms via deep learning detection, segmentation, and classification

MA Al-Antari, MA Al-Masni, MT Choi, SM Han… - International journal of …, 2018 - Elsevier
A computer-aided diagnosis (CAD) system requires detection, segmentation, and
classification in one framework to assist radiologists efficiently in an accurate diagnosis. In …

Breast cancer classification from histopathological images using patch-based deep learning modeling

I Hirra, M Ahmad, A Hussain, MU Ashraf… - IEEE …, 2021 - ieeexplore.ieee.org
Accurate detection and classification of breast cancer is a critical task in medical imaging
due to the complexity of breast tissues. Due to automatic feature extraction ability, deep …

Simultaneous detection and classification of breast masses in digital mammograms via a deep learning YOLO-based CAD system

MA Al-Masni, MA Al-Antari, JM Park, G Gi… - Computer methods and …, 2018 - Elsevier
Background and objective Automatic detection and classification of the masses in
mammograms are still a big challenge and play a crucial role to assist radiologists for …

YOLO based breast masses detection and classification in full-field digital mammograms

GH Aly, M Marey, SA El-Sayed, MF Tolba - Computer methods and …, 2021 - Elsevier
Abstract Background and Objective With the recent development in deep learning since
2012, the use of Convolutional Neural Networks (CNNs) in bioinformatics, especially …