Artificial intelligence for digital and computational pathology
Advances in digitizing tissue slides and the fast-paced progress in artificial intelligence,
including deep learning, have boosted the field of computational pathology. This field holds …
including deep learning, have boosted the field of computational pathology. This field holds …
Prediction of recurrence risk in endometrial cancer with multimodal deep learning
S Volinsky-Fremond, N Horeweg, S Andani… - Nature Medicine, 2024 - nature.com
Predicting distant recurrence of endometrial cancer (EC) is crucial for personalized adjuvant
treatment. The current gold standard of combined pathological and molecular profiling is …
treatment. The current gold standard of combined pathological and molecular profiling is …
A Systematic Review of Generalization Research in Medical Image Classification
S Matta, M Lamard, P Zhang, AL Guilcher… - arXiv preprint arXiv …, 2024 - arxiv.org
Numerous Deep Learning (DL) classification models have been developed for a large
spectrum of medical image analysis applications, which promises to reshape various facets …
spectrum of medical image analysis applications, which promises to reshape various facets …
[HTML][HTML] Mitosis detection, fast and slow: robust and efficient detection of mitotic figures
M Jahanifar, A Shephard, N Zamanitajeddin… - Medical Image …, 2024 - Elsevier
Counting of mitotic figures is a fundamental step in grading and prognostication of several
cancers. However, manual mitosis counting is tedious and time-consuming. In addition …
cancers. However, manual mitosis counting is tedious and time-consuming. In addition …
Domain generalization in computational pathology: survey and guidelines
Deep learning models have exhibited exceptional effectiveness in Computational Pathology
(CPath) by tackling intricate tasks across an array of histology image analysis applications …
(CPath) by tackling intricate tasks across an array of histology image analysis applications …
A deep learning framework deploying segment anything to detect pan-cancer mitotic figures from haematoxylin and eosin-stained slides
Mitotic activity is an important feature for grading several cancer types. However, counting
mitotic figures (cells in division) is a time-consuming and laborious task prone to inter …
mitotic figures (cells in division) is a time-consuming and laborious task prone to inter …
Stain-robust mitotic figure detection for MIDOG 2022 challenge
M Jahanifar, A Shephard, N Zamanitajeddin… - arXiv preprint arXiv …, 2022 - arxiv.org
The detection of mitotic figures from different scanners/sites remains an important topic of
research, owing to its potential in assisting clinicians with tumour grading. The MItosis …
research, owing to its potential in assisting clinicians with tumour grading. The MItosis …
Assessing domain adaptation techniques for mitosis detection in multi-scanner breast cancer histopathology images
Breast cancer is the most commonly diagnosed cancer worldwide, with over two million new
cases each year. During diagnostic tumour grading, pathologists manually count the number …
cases each year. During diagnostic tumour grading, pathologists manually count the number …
Detecting mitoses with a convolutional neural network for midog 2022 challenge
This work presents a mitosis detection method with only one vanilla Convolutional Neural
Network (CNN). Our method consists of two steps: given an image, we first apply a CNN …
Network (CNN). Our method consists of two steps: given an image, we first apply a CNN …
Domain-robust mitotic figure detection with style transfer
Recent studies for mitotic figure identification have shown performance comparable to that of
human experts; however, the challenge to develop strategies invariant to image variance in …
human experts; however, the challenge to develop strategies invariant to image variance in …