AIMC Topic: Histological Techniques

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Cellular community detection for tissue phenotyping in colorectal cancer histology images.

Medical image analysis Apr 13, 2020
Classification of various types of tissue in cancer histology images based on the cellular compositions is an important step towards the development of computational pathology tools for systematic digital profiling of the spatial tumor microenvironme...
Humans Neural Networks, Computer Tumor Microenvironment Cell Nucleus Histological Techniques Algorithms Colorectal Neoplasms
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Context-Aware Convolutional Neural Network for Grading of Colorectal Cancer Histology Images.

IEEE transactions on medical imaging Feb 3, 2020
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. 224×...
Histological Techniques Neural Networks, Computer Colorectal Neoplasms Humans
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Enabling a Single Deep Learning Model for Accurate Gland Instance Segmentation: A Shape-Aware Adversarial Learning Framework.

IEEE transactions on medical imaging Jan 14, 2020
Segmenting gland instances in histology images is highly challenging as it requires not only detecting glands from a complex background but also separating each individual gland instance with accurate boundary detection. However, due to the boundary ...
Histological Techniques Deep Learning
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Deep Learning-Based Classification of Liver Cancer Histopathology Images Using Only Global Labels.

IEEE journal of biomedical and health informatics Oct 28, 2019
Liver cancer is a leading cause of cancer deaths worldwide due to its high morbidity and mortality. Histopathological image analysis (HIA) is a crucial step in the early diagnosis of liver cancer and is routinely performed manually. However, this pro...
Deep Learning Liver Neoplasms Early Detection of Cancer Algorithms Databases, Factual Histological Techniques Liver Image Interpretation, Computer-Assisted Humans
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Computer-Aided Diagnosis in Histopathological Images of the Endometrium Using a Convolutional Neural Network and Attention Mechanisms.

IEEE journal of biomedical and health informatics Oct 1, 2019
Uterine cancer (also known as endometrial cancer) can seriously affect the female reproductive system, and histopathological image analysis is the gold standard for diagnosing endometrial cancer. Due to the limited ability to model the complicated re...
Humans Neural Networks, Computer Image Interpretation, Computer-Assisted Histological Techniques Sensitivity and Specificity Deep Learning Endometrium Algorithms Female
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Deep Learning-Based Gleason Grading of Prostate Cancer From Histopathology Images-Role of Multiscale Decision Aggregation and Data Augmentation.

IEEE journal of biomedical and health informatics Sep 30, 2019
Visual inspection of histopathology images of stained biopsy tissue by expert pathologists is the standard method for grading of prostate cancer (PCa). However, this process is time-consuming and subject to high inter-observer variability. Machine le...
Prostate Image Interpretation, Computer-Assisted Histological Techniques Deep Learning Prostatic Neoplasms Neoplasm Grading Humans Male
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Hover-Net: Simultaneous segmentation and classification of nuclei in multi-tissue histology images.

Medical image analysis Sep 18, 2019
Nuclear segmentation and classification within Haematoxylin & Eosin stained histology images is a fundamental prerequisite in the digital pathology work-flow. The development of automated methods for nuclear segmentation and classification enables th...
Humans Neural Networks, Computer Histological Techniques Adenocarcinoma Datasets as Topic Colorectal Neoplasms Staining and Labeling Cell Nucleus
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Utilizing supervised machine learning to identify microglia and astrocytes in situ: implications for large-scale image analysis and quantification.

Journal of neuroscience methods Sep 5, 2019
BACKGROUND: The evaluation of histological tissue samples plays a crucial role in deciphering preclinical disease and injury mechanisms. High-resolution images can be obtained quickly however data acquisition are often bottlenecked by manual analysis...
Animals, Genetically Modified Fluorescent Antibody Technique Neurosciences Histological Techniques Microglia Astrocytes Supervised Machine Learning Mice Rats Reproducibility of Results Animals Image Processing, Computer-Assisted Sensitivity and Specificity
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Impact of pre-analytical variables on deep learning accuracy in histopathology.

Histopathology May 16, 2019
AIMS: Machine learning (ML) binary classification in diagnostic histopathology is an area of intense investigation. Several assumptions, including training image quality/format and the number of training images required, appear to be similar in many ...
Female Male Diagnosis, Computer-Assisted Neural Networks, Computer Machine Learning Humans Deep Learning Pathology, Clinical Image Interpretation, Computer-Assisted Histological Techniques Histology
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Rapid histology of laryngeal squamous cell carcinoma with deep-learning based stimulated Raman scattering microscopy.

Theranostics Apr 13, 2019
Maximal resection of tumor while preserving the adjacent healthy tissue is particularly important for larynx surgery, hence precise and rapid intraoperative histology of laryngeal tissue is crucial for providing optimal surgical outcomes. We hypothes...
Histological Techniques Carcinoma, Squamous Cell Humans Nonlinear Optical Microscopy Laryngeal Neoplasms Deep Learning Pathology, Surgical Automation, Laboratory China
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