AIMC Topic: Histocytochemistry
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Unsupervised method for normalization of hematoxylin-eosin stain in histological images.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Aug 14, 2019
Histological images stained with hematoxylin-eosin are widely used by pathologists for cancer diagnosis. However, these images can have color variations that highly influence the histological image processing techniques. To deal with this potential l...
A deep learning algorithm for one-step contour aware nuclei segmentation of histopathology images.
Medical & biological engineering & computing
Jul 26, 2019
This paper addresses the task of nuclei segmentation in high-resolution histopathology images. We propose an automatic end-to-end deep neural network algorithm for segmentation of individual nuclei. A nucleus-boundary model is introduced to predict n...
Towards Fine Whole-Slide Skeletal Muscle Image Segmentation through Deep Hierarchically Connected Networks.
Journal of healthcare engineering
Jun 27, 2019
Automatic skeletal muscle image segmentation (MIS) is crucial in the diagnosis of muscle-related diseases. However, accurate methods often suffer from expensive computations, which are not scalable to large-scale, whole-slide muscle images. In this p...
Generative Adversarial Networks for Facilitating Stain-Independent Supervised and Unsupervised Segmentation: A Study on Kidney Histology.
IEEE transactions on medical imaging
Feb 14, 2019
A major challenge in the field of segmentation in digital pathology is given by the high effort for manual data annotations in combination with many sources introducing variability in the image domain. This requires methods that are able to cope with...
Fast ScanNet: Fast and Dense Analysis of Multi-Gigapixel Whole-Slide Images for Cancer Metastasis Detection.
IEEE transactions on medical imaging
Jan 7, 2019
Lymph node metastasis is one of the most important indicators in breast cancer diagnosis, that is traditionally observed under the microscope by pathologists. In recent years, with the dramatic advance of high-throughput scanning and deep learning te...
Unsupervised Feature Extraction via Deep Learning for Histopathological Classification of Colon Tissue Images.
IEEE transactions on medical imaging
Nov 2, 2018
Histopathological examination is today's gold standard for cancer diagnosis. However, this task is time consuming and prone to errors as it requires a detailed visual inspection and interpretation of a pathologist. Digital pathology aims at alleviati...
Sparse Representation Over Learned Dictionaries on the Riemannian Manifold for Automated Grading of Nuclear Pleomorphism in Breast Cancer.
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Oct 22, 2018
Breast cancer is found to be the most pervasive type of cancer among women. Computer aided detection and diagnosis of cancer at the initial stages can increase the chances of recovery and thus reduce the mortality rate through timely prognosis and ad...
Path R-CNN for Prostate Cancer Diagnosis and Gleason Grading of Histological Images.
IEEE transactions on medical imaging
Oct 12, 2018
Prostate cancer is the most common and second most deadly form of cancer in men in the United States. The classification of prostate cancers based on Gleason grading using histological images is important in risk assessment and treatment planning for...
Gastric Pathology Image Classification Using Stepwise Fine-Tuning for Deep Neural Networks.
Journal of healthcare engineering
Jun 21, 2018
Deep learning using convolutional neural networks (CNNs) is a distinguished tool for many image classification tasks. Due to its outstanding robustness and generalization, it is also expected to play a key role to facilitate advanced computer-aided d...
Segmentation of histological images and fibrosis identification with a convolutional neural network.
Computers in biology and medicine
May 16, 2018
Segmentation of histological images is one of the most crucial tasks for many biomedical analyses involving quantification of certain tissue types, such as fibrosis via Masson's trichrome staining. However, challenges are posed by the high variabilit...
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