AIMC Topic: Histocytochemistry
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A method for utilizing automated machine learning for histopathological classification of testis based on Johnsen scores.
Scientific reports
May 10, 2021
We examined whether a tool for determining Johnsen scores automatically using artificial intelligence (AI) could be used in place of traditional Johnsen scoring to support pathologists' evaluations. Average precision, precision, and recall were asses...
Artificial intelligence for cellular phenotyping diagnosis of nasal polyps by whole-slide imaging.
EBioMedicine
Apr 12, 2021
BACKGROUND: artificial intelligence (AI) for cellular phenotyping diagnosis of nasal polyps by whole-slide imaging (WSI) is lacking. We aim to establish an AI chronic rhinosinusitis evaluation platform 2.0 (AICEP 2.0) to obtain the proportion of infl...
GestAltNet: aggregation and attention to improve deep learning of gestational age from placental whole-slide images.
Laboratory investigation; a journal of technical methods and pathology
Mar 5, 2021
The placenta is the first organ to form and performs the functions of the lung, gut, kidney, and endocrine systems. Abnormalities in the placenta cause or reflect most abnormalities in gestation and can have life-long consequences for the mother and ...
Data-efficient and weakly supervised computational pathology on whole-slide images.
Nature biomedical engineering
Mar 1, 2021
Deep-learning methods for computational pathology require either manual annotation of gigapixel whole-slide images (WSIs) or large datasets of WSIs with slide-level labels and typically suffer from poor domain adaptation and interpretability. Here we...
PyHIST: A Histological Image Segmentation Tool.
PLoS computational biology
Oct 19, 2020
The development of increasingly sophisticated methods to acquire high-resolution images has led to the generation of large collections of biomedical imaging data, including images of tissues and organs. Many of the current machine learning methods th...
Using an ontology of the human cardiovascular system to improve the classification of histological images.
Scientific reports
Jul 23, 2020
The advantages of automatically recognition of fundamental tissues using computer vision techniques are well known, but one of its main limitations is that sometimes it is not possible to classify correctly an image because the visual information is ...
Evaluation of a Deep Neural Network for Automated Classification of Colorectal Polyps on Histopathologic Slides.
JAMA network open
Apr 1, 2020
IMPORTANCE: Histologic classification of colorectal polyps plays a critical role in screening for colorectal cancer and care of affected patients. An accurate and automated algorithm for the classification of colorectal polyps on digitized histopatho...
DeepSurvNet: deep survival convolutional network for brain cancer survival rate classification based on histopathological images.
Medical & biological engineering & computing
Mar 2, 2020
Histopathological whole slide images of haematoxylin and eosin (H&E)-stained biopsies contain valuable information with relation to cancer disease and its clinical outcomes. Still, there are no highly accurate automated methods to correlate histolopa...
ConvPath: A software tool for lung adenocarcinoma digital pathological image analysis aided by a convolutional neural network.
EBioMedicine
Nov 22, 2019
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 of the body, all of which represent key "hallmarks of cancer". Ho...
Weakly Supervised Deep Learning for Whole Slide Lung Cancer Image Analysis.
IEEE transactions on cybernetics
Sep 2, 2019
Histopathology image analysis serves as the gold standard for cancer diagnosis. Efficient and precise diagnosis is quite critical for the subsequent therapeutic treatment of patients. So far, computer-aided diagnosis has not been widely applied in pa...
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