[HTML][HTML] Computer-aided breast cancer detection and classification in mammography: A comprehensive review

K Loizidou, R Elia, C Pitris - Computers in Biology and Medicine, 2023 - Elsevier
Cancer is the second cause of mortality worldwide and it has been identified as a perilous
disease. Breast cancer accounts for∼ 20% of all new cancer cases worldwide, making it a …

Microcalcification discrimination in mammography using deep convolutional neural network: towards rapid and early breast cancer diagnosis

YS Leong, K Hasikin, KW Lai, N Mohd Zain… - Frontiers in public …, 2022 - frontiersin.org
Breast cancer is among the most common types of cancer in women and under the cases of
misdiagnosed, or delayed in treatment, the mortality risk is high. The existence of breast …

A novel machine learning approach on texture analysis for automatic breast microcalcification diagnosis classification of mammogram images

ZM Sarvestani, J Jamali, M Taghizadeh… - Journal of Cancer …, 2023 - Springer
Purpose Screening programs use mammography as a diagnostic tool for the early detection
of breast cancer. Mammogram enhancement is used to increase the local contrast of the …

Enhancing early breast cancer diagnosis through automated microcalcification detection using an optimized ensemble deep learning framework

JR Teoh, K Hasikin, KW Lai, X Wu, C Li - PeerJ Computer Science, 2024 - peerj.com
Background Breast cancer remains a pressing global health concern, necessitating accurate
diagnostics for effective interventions. Deep learning models (AlexNet, ResNet-50, VGG16 …

Transformer Models for Enhanced Calcifications Detection in Mammography

M Cantone, C Marrocco, F Tortorella, A Bria - International Conference on …, 2024 - Springer
In recent years, the image analysis landscape is witnessing a paradigm shift with the
emergence of the vision transformer as a better alternative to Convolutional Neural …

AI in Oncology: Transforming Cancer Detection through Machine Learning and Deep Learning Applications

M Aftab, F Mehmood, C Zhang, A Nadeem… - arXiv preprint arXiv …, 2025 - arxiv.org
Artificial intelligence (AI) has potential to revolutionize the field of oncology by enhancing the
precision of cancer diagnosis, optimizing treatment strategies, and personalizing therapies …

Analisa Gambar X-Ray Mammography dengan Convolution Neural Network pada Deep Learning dengan Arsitektur Resnet

NI Sanusi - ANALISA GAMBAR X-RAY MAMMOGRAPHY …, 2023 - repository.uin-suska.ac.id
Kanker adalah penyakit yang terjadi ketika sel-sel tubuh mengalami perubahan dan tumbuh
secara tidak terkendali. Kanker payudara merupakan salah satu jenis kanker yang umum …

Precancerous microcalcification detection of breast cancer mammogram images using linear time-invariant filtering Wiener method with Tophat transformation

R Jamil, M Dong, S Bano, A Javed, M Abdullah - 2023 - researchsquare.com
Breast microcalcifications, tiny calcium salt deposits, can develop anywhere in the breast
tissue. Breast microcalcifications are a frequent mammographic finding. For a proper …

[PDF][PDF] ResNet-101 Empowered Deep Learning for Breast Cancer Ultrasound Image Classification.

AC Yadav, MH Kolekar, MK Zope - BIOSTEC (1), 2024 - scitepress.org
In the modern era, accurate breast cancer classification plays a crucial role in early detection
and treatment planning. This article introduces a modified ResNet-101 architecture tailored …

Microcalcification detection in mammography for early breast cancer diagnosis using deep learning technique/Leong Yew Sum

YS Leong - 2022 - studentsrepo.um.edu.my
Breast Cancer is one of the common cancers in women and may cause lives to be lost if they
were misdiagnosed and left untreated. Existence of breast microcalcifications are common …