Artificial intelligence in lung cancer pathology image analysis
Objective: Accurate diagnosis and prognosis are essential in lung cancer treatment
selection and planning. With the rapid advance of medical imaging technology, whole slide …
selection and planning. With the rapid advance of medical imaging technology, whole slide …
[HTML][HTML] Artificial intelligence at the intersection of pathology and radiology in prostate cancer
SA Harmon, S Tuncer, T Sanford… - Diagnostic and …, 2019 - ncbi.nlm.nih.gov
Pathologic grading plays a key role in prostate cancer risk stratification and treatment
selection, traditionally assessed from systemic core needle biopsies sampled throughout the …
selection, traditionally assessed from systemic core needle biopsies sampled throughout the …
Automatic grading of prostate cancer in digitized histopathology images: Learning from multiple experts
Prostate cancer (PCa) is a heterogeneous disease that is manifested in a diverse range of
histologic patterns and its grading is therefore associated with an inter-observer variability …
histologic patterns and its grading is therefore associated with an inter-observer variability …
Two path gland segmentation algorithm of colon pathological image based on local semantic guidance
Colonic adenocarcinoma is a disease severely endangering human life caused by mucosal
epidermal carcinogenesis. The segmentation of potentially cancerous glands is the key in …
epidermal carcinogenesis. The segmentation of potentially cancerous glands is the key in …
Comparison of artificial intelligence techniques to evaluate performance of a classifier for automatic grading of prostate cancer from digitized histopathologic images
Importance Proper evaluation of the performance of artificial intelligence techniques in the
analysis of digitized medical images is paramount for the adoption of such techniques by the …
analysis of digitized medical images is paramount for the adoption of such techniques by the …
ConvPath: a software tool for lung adenocarcinoma digital pathological image analysis aided by a convolutional neural network
Background The spatial distributions of different types of cells could reveal a cancer cell's
growth pattern, its relationships with the tumor microenvironment and the immune response …
growth pattern, its relationships with the tumor microenvironment and the immune response …
Multi-scale fully convolutional network for gland segmentation using three-class classification
H Ding, Z Pan, Q Cen, Y Li, S Chen - Neurocomputing, 2020 - Elsevier
Automated precise segmentation of glands from the histological images plays an important
role in glandular morphology analysis, which is a crucial criterion for cancer grading and …
role in glandular morphology analysis, which is a crucial criterion for cancer grading and …
Feature-driven local cell graph (FLocK): new computational pathology-based descriptors for prognosis of lung cancer and HPV status of oropharyngeal cancers
Local spatial arrangement of nuclei in histopathology images of different cancer subtypes
has been shown to have prognostic value. In order to capture localized nuclear architectural …
has been shown to have prognostic value. In order to capture localized nuclear architectural …
Automated detection of DCIS in whole-slide H&E stained breast histopathology images
BE Bejnordi, M Balkenhol, G Litjens… - IEEE transactions on …, 2016 - ieeexplore.ieee.org
This paper presents and evaluates a fully automatic method for detection of ductal
carcinoma in situ (DCIS) in digitized hematoxylin and eosin (H&E) stained histopathological …
carcinoma in situ (DCIS) in digitized hematoxylin and eosin (H&E) stained histopathological …
Luminal water imaging: a new MR imaging T2 mapping technique for prostate cancer diagnosis
Purpose To assess the feasibility of luminal water imaging, a quantitative T2-based
magnetic resonance (MR) imaging technique, for the detection and grading of prostate …
magnetic resonance (MR) imaging technique, for the detection and grading of prostate …