A comprehensive review of computer-aided whole-slide image analysis: from datasets to feature extraction, segmentation, classification and detection approaches
With the development of Computer-aided Diagnosis (CAD) and image scanning techniques,
Whole-slide Image (WSI) scanners are widely used in the field of pathological diagnosis …
Whole-slide Image (WSI) scanners are widely used in the field of pathological diagnosis …
The devil is in the details: Whole slide image acquisition and processing for artifacts detection, color variation, and data augmentation: A review
Whole Slide Images (WSI) are widely used in histopathology for research and the diagnosis
of different types of cancer. The preparation and digitization of histological tissues leads to …
of different types of cancer. The preparation and digitization of histological tissues leads to …
Federated learning for predicting histological response to neoadjuvant chemotherapy in triple-negative breast cancer
J Ogier du Terrail, A Leopold, C Joly, C Béguier… - Nature medicine, 2023 - nature.com
Triple-negative breast cancer (TNBC) is a rare cancer, characterized by high metastatic
potential and poor prognosis, and has limited treatment options. The current standard of …
potential and poor prognosis, and has limited treatment options. The current standard of …
Medical image analysis based on deep learning approach
M Puttagunta, S Ravi - Multimedia tools and applications, 2021 - Springer
Medical imaging plays a significant role in different clinical applications such as medical
procedures used for early detection, monitoring, diagnosis, and treatment evaluation of …
procedures used for early detection, monitoring, diagnosis, and treatment evaluation of …
Breast cancer histopathology image classification using an ensemble of deep learning models
Breast cancer is one of the major public health issues and is considered a leading cause of
cancer-related deaths among women worldwide. Its early diagnosis can effectively help in …
cancer-related deaths among women worldwide. Its early diagnosis can effectively help in …
A deep learning method for breast cancer classification in the pathology images
Objective: Breast cancer is the most common female cancer in the world, and it poses a
huge threat to women's health. There is currently promising research concerning its early …
huge threat to women's health. There is currently promising research concerning its early …
Deep learning-based breast cancer grading and survival analysis on whole-slide histopathology images
Breast cancer tumor grade is strongly associated with patient survival. In current clinical
practice, pathologists assign tumor grade after visual analysis of tissue specimens …
practice, pathologists assign tumor grade after visual analysis of tissue specimens …
Artificial intelligence-assisted diagnostic cytology and genomic testing for hematologic disorders
L Gedefaw, CF Liu, RKL Ip, HF Tse, MHY Yeung… - Cells, 2023 - mdpi.com
Artificial intelligence (AI) is a rapidly evolving field of computer science that involves the
development of computational programs that can mimic human intelligence. In particular …
development of computational programs that can mimic human intelligence. In particular …
Siloed federated learning for multi-centric histopathology datasets
M Andreux, JO du Terrail, C Beguier… - Domain Adaptation and …, 2020 - Springer
While federated learning is a promising approach for training deep learning models over
distributed sensitive datasets, it presents new challenges for machine learning, especially …
distributed sensitive datasets, it presents new challenges for machine learning, especially …
[图书][B] Deep learning for medical image analysis
Deep Learning for Medical Image Analysis, Second Edition is a great learning resource for
academic and industry researchers and graduate students taking courses on machine …
academic and industry researchers and graduate students taking courses on machine …