AIMC Topic: Histological Techniques

Clear Filters Showing 1 to 10 of 78 articles

FedDBL: Communication and Data Efficient Federated Deep-Broad Learning for Histopathological Tissue Classification.

IEEE transactions on cybernetics Nov 27, 2024
Histopathological tissue classification is a fundamental task in computational pathology. Deep learning (DL)-based models have achieved superior performance but centralized training suffers from the privacy leakage problem. Federated learning (FL) ca...
Humans Image Interpretation, Computer-Assisted Histological Techniques Deep Learning Algorithms
View on PubMed DOI

Sliding Window Optimal Transport for Open World Artifact Detection in Histopathology.

IEEE journal of biomedical and health informatics Jul 2, 2024
Histological images are frequently impaired by local artifacts from scanner malfunctions or iatrogenic processes - caused by preparation - impacting the performance of Deep Learning models. Models often struggle with the slightest out-of-distribution...
Histological Techniques Humans Image Processing, Computer-Assisted Algorithms Histocytochemistry Deep Learning Image Interpretation, Computer-Assisted Artifacts
View on PubMed DOI

Registered multi-device/staining histology image dataset for domain-agnostic machine learning models.

Scientific data Apr 3, 2024
Variations in color and texture of histopathology images are caused by differences in staining conditions and imaging devices between hospitals. These biases decrease the robustness of machine learning models exposed to out-of-domain data. To address...
Neural Networks, Computer Machine Learning Humans Histological Techniques Histology Staining and Labeling Image Processing, Computer-Assisted Eosine Yellowish-(YS)
View on PubMed DOI

Protocol for automated multivariate quantitative-image-based cytometry analysis by fluorescence microscopy of asynchronous adherent cells.

STAR protocols Jul 13, 2023
Here, we present a protocol for multivariate quantitative-image-based cytometry (QIBC) analysis by fluorescence microscopy of asynchronous adherent cells. We describe steps for the preparation, treatment, and fixation of cells, sample staining, and i...
Cell Nucleus Microscopy, Fluorescence Data Visualization Histological Techniques Artificial Intelligence
View on PubMed DOI

ChampKit: A framework for rapid evaluation of deep neural networks for patch-based histopathology classification.

Computer methods and programs in biomedicine May 30, 2023
BACKGROUND AND OBJECTIVE: Histopathology is the gold standard for diagnosis of many cancers. Recent advances in computer vision, specifically deep learning, have facilitated the analysis of histopathology images for many tasks, including the detectio...
Humans Histological Techniques Neoplasms Software Algorithms Neural Networks, Computer
View on PubMed DOI

Cancer prediction from few amounts of histology samples through self-attention based multi-routines cross-domains network.

Physics in medicine and biology May 22, 2023
OBJECTIVE: Rapid and efficient analysis of cancer has become a focus of research. Artificial intelligence can use histopathological data to quickly determine the cancer situation, but still faces challenges. For example, the convolutional network is ...
Histological Techniques Neoplasms Artificial Intelligence Humans
View on PubMed DOI

[Development of the use of artificial intelligence in the management of chronic inflammatory bowel disease].

Annales de pathologie Mar 28, 2023
Complexity of inflammatory bowel diseases (IBD) lies on their management and their biology. Clinics, blood and fecal samples tests, endoscopy and histology are the main tools guiding IBD treatment, but they generate a large amount of data, difficult ...
Intestines Feces Histological Techniques Artificial Intelligence Inflammatory Bowel Diseases Humans
View on PubMed DOI

Identify Representative Samples by Conditional Random Field of Cancer Histology Images.

IEEE transactions on medical imaging Dec 2, 2022
Pathology analysis is crucial to precise cancer diagnoses and the succeeding treatment plan as well. To detect abnormality in histopathology images with prevailing patch-based convolutional neural networks (CNNs), contextual information often serves ...
Neoplasms Histological Techniques Neural Networks, Computer Humans
View on PubMed DOI

Fast and scalable search of whole-slide images via self-supervised deep learning.

Nature biomedical engineering Oct 10, 2022
The adoption of digital pathology has enabled the curation of large repositories of gigapixel whole-slide images (WSIs). Computationally identifying WSIs with similar morphologic features within large repositories without requiring supervised trainin...
Deep Learning Humans Histological Techniques Algorithms
View on PubMed DOI

Perception without preconception: comparison between the human and machine learner in recognition of tissues from histological sections.

Scientific reports Sep 30, 2022
Deep neural networks (DNNs) have shown success in image classification, with high accuracy in recognition of everyday objects. Performance of DNNs has traditionally been measured assuming human accuracy is perfect. In specific problem domains, howeve...
Perception Humans Histological Techniques Machine Learning Neural Networks, Computer
View on PubMed DOI
Popular Topics
Recent Journals