Transfer learning techniques for medical image analysis: A review
Medical imaging is a useful tool for disease detection and diagnostic imaging technology
has enabled early diagnosis of medical conditions. Manual image analysis methods are …
has enabled early diagnosis of medical conditions. Manual image analysis methods are …
Developing image analysis methods for digital pathology
P Bankhead - The Journal of pathology, 2022 - Wiley Online Library
The potential to use quantitative image analysis and artificial intelligence is one of the
driving forces behind digital pathology. However, despite novel image analysis methods for …
driving forces behind digital pathology. However, despite novel image analysis methods for …
On the analyses of medical images using traditional machine learning techniques and convolutional neural networks
Convolutional neural network (CNN) has shown dissuasive accomplishment on different
areas especially Object Detection, Segmentation, Reconstruction (2D and 3D), Information …
areas especially Object Detection, Segmentation, Reconstruction (2D and 3D), Information …
Automatic diagnosis and grading of prostate cancer with weakly supervised learning on whole slide images
Background: The workflow of prostate cancer diagnosis and grading is cumbersome and the
results suffer from substantial inter-observer variability. Recent trials have shown potential in …
results suffer from substantial inter-observer variability. Recent trials have shown potential in …
AI-based carcinoma detection and classification using histopathological images: A systematic review
Histopathological image analysis is the gold standard to diagnose cancer. Carcinoma is a
subtype of cancer that constitutes more than 80% of all cancer cases. Squamous cell …
subtype of cancer that constitutes more than 80% of all cancer cases. Squamous cell …
Prostate cancer histopathology using label-free multispectral deep-UV microscopy quantifies phenotypes of tumor aggressiveness and enables multiple diagnostic …
Identifying prostate cancer patients that are harboring aggressive forms of prostate cancer
remains a significant clinical challenge. Here we develop an approach based on …
remains a significant clinical challenge. Here we develop an approach based on …
Whole slide image quality in digital pathology: review and perspectives
R Brixtel, S Bougleux, O Lézoray, Y Caillot… - IEEE …, 2022 - ieeexplore.ieee.org
With the advent of whole slide image (WSI) scanners, pathology is undergoing a digital
revolution. Simultaneously, with the development of image analysis algorithms based on …
revolution. Simultaneously, with the development of image analysis algorithms based on …
[HTML][HTML] Artificial intelligence-based prediction for cancer-related outcomes in Africa: status and potential refinements
2021 Deep learning Detection of HSIL and LSIL in cervical cancer Phase I-III Internal
0.97[18] 2018 Machine learning Breast cancer staging Phase I, II, IV NIL 0.84[19] 2021 …
0.97[18] 2018 Machine learning Breast cancer staging Phase I, II, IV NIL 0.84[19] 2021 …
Prostate cancer grading framework based on deep transfer learning and Aquila optimizer
Prostate cancer is the one of the most dominant cancer among males. It represents one of
the leading cancer death causes worldwide. Due to the current evolution of artificial …
the leading cancer death causes worldwide. Due to the current evolution of artificial …
[HTML][HTML] ProGleason-GAN: Conditional progressive growing GAN for prostatic cancer Gleason grade patch synthesis
A Golfe, R Del Amor, A Colomer, MA Sales… - Computer Methods and …, 2023 - Elsevier
Background and objective Prostate cancer is one of the most common diseases affecting
men. The main diagnostic and prognostic reference tool is the Gleason scoring system. An …
men. The main diagnostic and prognostic reference tool is the Gleason scoring system. An …