AI Medical Compendium Journal:
The journal of pathology. Clinical research

Showing 1 to 10 of 20 articles

Engineering the future of 3D pathology.

The journal of pathology. Clinical research
In recent years, technological advances in tissue preparation, high-throughput volumetric microscopy, and computational infrastructure have enabled rapid developments in nondestructive 3D pathology, in which high-resolution histologic datasets are ob...

Identifying primary tumor site of origin for liver metastases via a combination of handcrafted and deep learning features.

The journal of pathology. Clinical research
Liver is one of the most common sites for metastases, which can occur on account of primary tumors from multiple sites of origin. Identifying the primary site of origin (PSO) of a metastasis can help in guiding therapeutic options for liver metastase...

Explainability and causability in digital pathology.

The journal of pathology. Clinical research
The current move towards digital pathology enables pathologists to use artificial intelligence (AI)-based computer programmes for the advanced analysis of whole slide images. However, currently, the best-performing AI algorithms for image analysis ar...

Deep learning-based image analysis reveals significant differences in the number and distribution of mucosal CD3 and γδ T cells between Crohn's disease and ulcerative colitis.

The journal of pathology. Clinical research
Colon mucosae of ulcerative colitis (UC) and Crohn's disease (CD) display differences in the number and distribution of immune cells that are difficult to assess by eye. Deep learning-based analysis on whole slide images (WSIs) allows extraction of c...

Optimization of deep learning models for the prediction of gene mutations using unsupervised clustering.

The journal of pathology. Clinical research
Deep learning models are increasingly being used to interpret whole-slide images (WSIs) in digital pathology and to predict genetic mutations. Currently, it is commonly assumed that tumor regions have most of the predictive power. However, it is reas...

Spatial analysis of tumor-infiltrating lymphocytes in histological sections using deep learning techniques predicts survival in colorectal carcinoma.

The journal of pathology. Clinical research
This study aimed to explore the prognostic impact of spatial distribution of tumor-infiltrating lymphocytes (TILs) quantified by deep learning (DL) approaches based on digitalized whole-slide images stained with hematoxylin and eosin in patients with...

The ethical challenges of artificial intelligence-driven digital pathology.

The journal of pathology. Clinical research
Digital pathology - the digitalisation of clinical histopathology services through the scanning and storage of pathology slides - has opened up new possibilities for health care in recent years, particularly in the opportunities it brings for artific...

Semantic annotation for computational pathology: multidisciplinary experience and best practice recommendations.

The journal of pathology. Clinical research
Recent advances in whole-slide imaging (WSI) technology have led to the development of a myriad of computer vision and artificial intelligence-based diagnostic, prognostic, and predictive algorithms. Computational Pathology (CPath) offers an integrat...

Automated annotations of epithelial cells and stroma in hematoxylin-eosin-stained whole-slide images using cytokeratin re-staining.

The journal of pathology. Clinical research
The diagnosis of solid tumors of epithelial origin (carcinomas) represents a major part of the workload in clinical histopathology. Carcinomas consist of malignant epithelial cells arranged in more or less cohesive clusters of variable size and shape...

Quick Annotator: an open-source digital pathology based rapid image annotation tool.

The journal of pathology. Clinical research
Image-based biomarker discovery typically requires accurate segmentation of histologic structures (e.g. cell nuclei, tubules, and epithelial regions) in digital pathology whole slide images (WSIs). Unfortunately, annotating each structure of interest...