Digital pathology and artificial intelligence

MKK Niazi, AV Parwani, MN Gurcan - The lancet oncology, 2019 - thelancet.com
In modern clinical practice, digital pathology has a crucial role and is increasingly a
technological requirement in the scientific laboratory environment. The advent of whole-slide …

Robust nucleus/cell detection and segmentation in digital pathology and microscopy images: a comprehensive review

F **ng, L Yang - IEEE reviews in biomedical engineering, 2016 - ieeexplore.ieee.org
Digital pathology and microscopy image analysis is widely used for comprehensive studies
of cell morphology or tissue structure. Manual assessment is labor intensive and prone to …

Breast cancer histopathology image analysis: A review

M Veta, JPW Pluim, PJ Van Diest… - IEEE transactions on …, 2014 - ieeexplore.ieee.org
This paper presents an overview of methods that have been proposed for the analysis of
breast cancer histopathology images. This research area has become particularly relevant …

Methods for nuclei detection, segmentation, and classification in digital histopathology: a review—current status and future potential

H Irshad, A Veillard, L Roux… - IEEE reviews in …, 2013 - ieeexplore.ieee.org
Digital pathology represents one of the major evolutions in modern medicine. Pathological
examinations constitute the gold standard in many medical protocols, and also play a critical …

Automatic nuclei segmentation in H&E stained breast cancer histopathology images

M Veta, PJ Van Diest, R Kornegoor, A Huisman… - PloS one, 2013 - journals.plos.org
The introduction of fast digital slide scanners that provide whole slide images has led to a
revival of interest in image analysis applications in pathology. Segmentation of cells and …

Application of feature extraction and classification methods for histopathological image using GLCM, LBP, LBGLCM, GLRLM and SFTA

Ş Öztürk, B Akdemir - Procedia computer science, 2018 - Elsevier
Classification of histopathologic images and identification of cancerous areas is quite
challenging due to image background complexity and resolution. The difference between …

Automated classification of brain tumor type in whole-slide digital pathology images using local representative tiles

J Barker, A Hoogi, A Depeursinge, DL Rubin - Medical image analysis, 2016 - Elsevier
Computerized analysis of digital pathology images offers the potential of improving clinical
care (eg automated diagnosis) and catalyzing research (eg discovering disease subtypes) …

Partitioning histopathological images: an integrated framework for supervised color-texture segmentation and cell splitting

H Kong, M Gurcan… - IEEE transactions on …, 2011 - ieeexplore.ieee.org
For quantitative analysis of histopathological images, such as the lymphoma grading
systems, quantification of features is usually carried out on single cells before categorizing …

[HTML][HTML] Artificial intelligence and digital microscopy applications in diagnostic hematopathology

H El Achi, JD Khoury - Cancers, 2020 - mdpi.com
Digital Pathology is the process of converting histology glass slides to digital images using
sophisticated computerized technology to facilitate acquisition, evaluation, storage, and …

A survey on automated cancer diagnosis from histopathology images

J Angel Arul Jothi, V Mary Anita Rajam - Artificial Intelligence Review, 2017 - Springer
Detecting cancer at an early stage is useful in better patient prognosis and treatment
planning. Even though there are several preliminary tests and non-invasive procedures that …