[HTML][HTML] Transfer learning for medical image classification: a literature review
HE Kim, A Cosa-Linan, N Santhanam, M Jannesari… - BMC medical …, 2022 - Springer
Background Transfer learning (TL) with convolutional neural networks aims to improve
performances on a new task by leveraging the knowledge of similar tasks learned in …
performances on a new task by leveraging the knowledge of similar tasks learned in …
[HTML][HTML] Digital pathology and computational image analysis in nephropathology
The emergence of digital pathology—an image-based environment for the acquisition,
management and interpretation of pathology information supported by computational …
management and interpretation of pathology information supported by computational …
The Banff 2019 Kidney Meeting Report (I): Updates on and clarification of criteria for T cell–and antibody‐mediated rejection
The XV. Banff conference for allograft pathology was held in conjunction with the annual
meeting of the American Society for Histocompatibility and Immunogenetics in Pittsburgh …
meeting of the American Society for Histocompatibility and Immunogenetics in Pittsburgh …
Transfer learning for medical images analyses: A survey
The advent of deep learning has brought great change to the community of computer
science and also revitalized numerous fields where traditional machine learning methods …
science and also revitalized numerous fields where traditional machine learning methods …
[HTML][HTML] Thirty years of the International Banff Classification for Allograft Pathology: the past, present, and future of kidney transplant diagnostics
Abstract 2021 marks the 30th anniversary of the original development of the Banff
Classification of Kidney Allograft Pathology, when in August 1991 a group of pathologists …
Classification of Kidney Allograft Pathology, when in August 1991 a group of pathologists …
[HTML][HTML] Development and evaluation of deep learning–based segmentation of histologic structures in the kidney cortex with multiple histologic stains
The application of deep learning for automated segmentation (delineation of boundaries) of
histologic primitives (structures) from whole slide images can facilitate the establishment of …
histologic primitives (structures) from whole slide images can facilitate the establishment of …
Glomerulosclerosis identification in whole slide images using semantic segmentation
G Bueno, MM Fernandez-Carrobles… - Computer methods and …, 2020 - Elsevier
Abstract Background and Objective: Glomeruli identification, ie, detection and
characterization, is a key procedure in many nephropathology studies. In this paper …
characterization, is a key procedure in many nephropathology studies. In this paper …
[HTML][HTML] Automation of the kidney function prediction and classification through ultrasound-based kidney imaging using deep learning
Prediction of kidney function and chronic kidney disease (CKD) through kidney ultrasound
imaging has long been considered desirable in clinical practice because of its safety …
imaging has long been considered desirable in clinical practice because of its safety …
A comprehensive survey of deep learning research on medical image analysis with focus on transfer learning
This survey aims to identify commonly used methods, datasets, future trends, knowledge
gaps, constraints, and limitations in the field to provide an overview of current solutions used …
gaps, constraints, and limitations in the field to provide an overview of current solutions used …
[HTML][HTML] Segmentation of glomeruli within trichrome images using deep learning
S Kannan, LA Morgan, B Liang, MKG Cheung… - Kidney international …, 2019 - Elsevier
Introduction The number of glomeruli and glomerulosclerosis evaluated on kidney biopsy
slides constitute standard components of a renal pathology report. Prevailing methods for …
slides constitute standard components of a renal pathology report. Prevailing methods for …