Context-Aware Convolutional Neural Network for Grading of Colorectal Cancer Histology Images [PDF]
Digital histology images are amenable to the application of convolutional neural networks (CNNs) for analysis due to the sheer size of pixel data present in them. CNNs are generally used for representation learning from small image patches (e.g.
M. Shaban +6 more
semanticscholar +1 more source
Comparative Histological Study on the Possible Effect of Adipose-Derived Mesenchymal Stem Cells versus Platelet Rich Plasma in Adriamycin-Induced Chronic Kidney Disease in Adult Male Albino Rat [PDF]
Introduction: Chronic kidney disease (CKD) is a worldwide health problem with rising morbidity & mortality. So, this model was performed to compare the possible effect of adipose tissue-derived stem cells against platelet-rich plasma on CKD induced ...
Hala Mohamed +3 more
doaj +1 more source
Prevalence of Helicobacter pylori in patients with gastro-oesophageal reflux disease : systematic review. [PDF]
Objectives: To ascertain the prevalence of Helicobacter pylori in patients with gastro-oesophageal reflux disease and its association with the disease.
Childs, S. +3 more
core +2 more sources
Predicting survival from colorectal cancer histology slides using deep learning: A retrospective multicenter study [PDF]
BACKGROUND: For virtually every patient with colorectal cancer (CRC), hematoxylin-eosin (HE)-stained tissue slides are available. These images contain quantitative information, which is not routinely used to objectively extract prognostic biomarkers.
Brenner, H. +17 more
core +2 more sources
IVUS-based histology of atherosclerotic plaques: improving longitudinal resolution [PDF]
Although Virtual Histology (VH) is the in-vivo gold standard for atherosclerosis plaque characterization in IVUS images, it suffers from a poor longitudinal resolution due to ECG-gating. In this paper, we propose an image- based approach to overcome this
Navab, Nassir +5 more
core +1 more source
Virtual staining for histology by deep learning.
In pathology and biomedical research, histology is the cornerstone method for tissue analysis. Currently, the histological workflow consumes plenty of chemicals, water, and time for staining procedures.
Leena Latonen +3 more
semanticscholar +1 more source
Structured crowdsourcing enables convolutional segmentation of histology images
Motivation While deep-learning algorithms have demonstrated outstanding performance in semantic image segmentation tasks, large annotation datasets are needed to create accurate models.
M. Amgad +30 more
semanticscholar +1 more source
ABSTRACT Pediatric gastroenteropancreatic neuroendocrine neoplasms (GEP‐NENs) are extremely rare and clinically heterogeneous. Management has largely been extrapolated from adult practice. This European Standard Clinical Practice Guideline (ESCP), developed by the EXPeRT network in collaboration with adult NEN experts, provides (adult) evidence ...
Michaela Kuhlen +23 more
wiley +1 more source
A Morphological and Histological Investigation of the Sinus Interdigitalis in Konya Merino Sheep
In the study, it was aimed to reveal the morphological, morphometric and histological characteristics of sinus interdigitalis found in the fore and hind feet of Konya merino sheep.
Zekeriya Özüdoğru +2 more
doaj +1 more source

