[HTML][HTML] A comprehensive review of deep neural networks for medical image processing: Recent developments and future opportunities
Artificial Intelligence (AI) solutions have been widely used in healthcare, and recent
developments in deep neural networks have contributed to significant advances in medical …
developments in deep neural networks have contributed to significant advances in medical …
A survey on artificial intelligence in histopathology image analysis
The increasing adoption of the whole slide image (WSI) technology in histopathology has
dramatically transformed pathologists' workflow and allowed the use of computer systems in …
dramatically transformed pathologists' workflow and allowed the use of computer systems in …
DigestPath: A benchmark dataset with challenge review for the pathological detection and segmentation of digestive-system
Examination of pathological images is the golden standard for diagnosing and screening
many kinds of cancers. Multiple datasets, benchmarks, and challenges have been released …
many kinds of cancers. Multiple datasets, benchmarks, and challenges have been released …
ANHIR: automatic non-rigid histological image registration challenge
Automatic Non-rigid Histological Image Registration (ANHIR) challenge was organized to
compare the performance of image registration algorithms on several kinds of microscopy …
compare the performance of image registration algorithms on several kinds of microscopy …
MVFStain: multiple virtual functional stain histopathology images generation based on specific domain mapping
To the best of our knowledge, artificial intelligence stain generation is an urgent requirement
for histopathology images. Pathological examinations usually only utilize hematoxylin and …
for histopathology images. Pathological examinations usually only utilize hematoxylin and …
DeepHistReg: Unsupervised deep learning registration framework for differently stained histology samples
M Wodzinski, H Müller - Computer methods and programs in biomedicine, 2021 - Elsevier
Background and objective The use of several stains during histology sample preparation
can be useful for fusing complementary information about different tissue structures. It …
can be useful for fusing complementary information about different tissue structures. It …
Radiological feature heterogeneity supports etiological diversity among patient groups in Meniere's disease
D Bächinger, N Filidoro, M Naville, N Juchler… - Scientific Reports, 2023 - nature.com
We aimed to determine the prevalence of radiological temporal bone features that in
previous studies showed only a weak or an inconsistent association with the clinical …
previous studies showed only a weak or an inconsistent association with the clinical …
Diffeomorphic registration with intensity transformation and missing data: Application to 3D digital pathology of Alzheimer's disease
This paper examines the problem of diffeomorphic image registration in the presence of
differing image intensity profiles and sparsely sampled, missing, or damaged tissue. Our …
differing image intensity profiles and sparsely sampled, missing, or damaged tissue. Our …
Multistep, automatic and nonrigid image registration method for histology samples acquired using multiple stains
M Wodzinski, A Skalski - Physics in Medicine & Biology, 2021 - iopscience.iop.org
The use of multiple dyes during histological sample preparation can reveal distinct tissue
properties. However, since the slide preparation differs for each dye, the tissue slides are …
properties. However, since the slide preparation differs for each dye, the tissue slides are …
Elastic transformation of histological slices allows precise co-registration with microCT data sets for a refined virtual histology approach
J Albers, A Svetlove, J Alves, A Kraupner, F di Lillo… - Scientific Reports, 2021 - nature.com
Although X-ray based 3D virtual histology is an emerging tool for the analysis of biological
tissue, it falls short in terms of specificity when compared to conventional histology. Thus, the …
tissue, it falls short in terms of specificity when compared to conventional histology. Thus, the …