ArticleThe journal of pathology. Clinical research2024
Engineering the future of 3D pathology.
Article in The journal of pathology. Clinical research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
14 citing papers in PubMed.
- Deep-learning triage of three-dimensional pathology datasets for comprehensive and efficient pathologist assessments.Nature biomedical engineering · 2026Article
- Assessing the Effects of a 3-Dimensional (3D) Pathology Tissue-Processing Workflow on Downstream Molecular Analyses.Laboratory investigation; a journal of technical methods and pathology · 2026Article
- Prototype-based AI triage for 3D pathology.bioRxiv : the preprint server for biology · 2026Article
- Scalable 3D cell-interaction analysis via supercell graphs for prostate cancer risk stratification.bioRxiv : the preprint server for biology · 2026Article
- Three-dimensional reconstruction of gigapixel whole-mount histopathology specimens with RAPID.Scientific reports · 2026Article
- 3D reconstruction of human liver tissue at cellular resolution.Science advances · 2026Article
- COEXIST: Coordinated single-cell integration of serial multiplexed tissue images.PLoS computational biology · 2025Article
- Delivery of a fibrin-binding hemostatic polymer ameliorates neurovascular damage and neural tissue loss after traumatic brain injury.Science advances · 2025Article
- Three-dimensional assessments are necessary to determine the true, spatially resolved composition of tissues.Cell reports methods · 2025Article
- Distributed and networked analysis of volumetric image data for remote collaboration of microscopy image analysis.Journal of medical imaging (Bellingham, Wash.) · 2025Article
- PanIN or IPMN? Redefining Lesion Size in 3 Dimensions.The American journal of surgical pathology · 2024Article
- Article
- Three-dimensional reconstruction of fetal rhesus macaque kidneys at single-cell resolution reveals complex inter-relation of structures.bioRxiv : the preprint server for biology · 2024Article
- Computational pathology in bladder cancer: A scoping review.Bladder cancer (Amsterdam, Netherlands)Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
Abstract
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 obtained from thick tissue specimens, such as whole biopsies, without the need for physical sectioning onto glass slides. While 3D pathology generates massive datasets that are attractive for automated computational analysis, there is also a desire to use 3D pathology to improve the visual assessment of tissue histology. In this perspective, we discuss and provide examples of potential advantages of 3D pathology for the visual assessment of clinical specimens and the challenges of dealing with large 3D datasets (of individual or multiple specimens) that pathologists have not been trained to interpret. We discuss the need for artificial intelligence triaging algorithms and explainable analysis methods to assist pathologists or other domain experts in the interpretation of these novel, often complex, large datasets.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.