Results: 24
Special Issue on Digital Pathology, Tissue Image Analysis, Artificial Intelligence, and Machine Learning: Approximation of the Effect of Novel Technologies on Toxicologic Pathology.
- Published in:
- Toxicologic Pathology, 2021, v. 49, n. 4, p. 705, doi. 10.1177/0192623321993756
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- Publication type:
- Article
HistoNet: A Deep Learning-Based Model of Normal Histology.
- Published in:
- Toxicologic Pathology, 2021, v. 49, n. 4, p. 784, doi. 10.1177/0192623321993425
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- Publication type:
- Article
Quantitative Assessment of Neuroinflammation, Myelinogenesis, Demyelination, and Nerve Fiber Regeneration in Immunostained Sciatic Nerves From Twitcher Mice With a Tissue Image Analysis Platform.
- Published in:
- Toxicologic Pathology, 2021, v. 49, n. 4, p. 950, doi. 10.1177/0192623321991469
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- Publication type:
- Article
Mini Review: The Last Mile—Opportunities and Challenges for Machine Learning in Digital Toxicologic Pathology.
- Published in:
- Toxicologic Pathology, 2021, v. 49, n. 4, p. 714, doi. 10.1177/0192623321990375
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- Publication type:
- Article
IMI—Bigpicture: A Central Repository for Digital Pathology.
- Published in:
- 2021
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- Publication type:
- Editorial
Proof of Concept for a Deep Learning Algorithm for Identification and Quantification of Key Microscopic Features in the Murine Model of DSS-Induced Colitis.
- Published in:
- Toxicologic Pathology, 2021, v. 49, n. 4, p. 897, doi. 10.1177/0192623320987804
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- Publication type:
- Article
Biomarker-Based Classification and Localization of Renal Lesions Using Learned Representations of Histology—A Machine Learning Approach to Histopathology.
- Published in:
- Toxicologic Pathology, 2021, v. 49, n. 4, p. 798, doi. 10.1177/0192623320987202
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- Publication type:
- Article
Evaluation of the Use of Single- and Multi-Magnification Convolutional Neural Networks for the Determination and Quantitation of Lesions in Nonclinical Pathology Studies.
- Published in:
- Toxicologic Pathology, 2021, v. 49, n. 4, p. 815, doi. 10.1177/0192623320986423
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- Publication type:
- Article
Proof of Concept: The Use of Whole-Slide Images (WSI) for Peer Review of Tissues on Routine Regulatory Toxicology Studies.
- Published in:
- Toxicologic Pathology, 2021, v. 49, n. 4, p. 750, doi. 10.1177/0192623320983252
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- Publication type:
- Article
Using Artificial Intelligence to Detect, Classify, and Objectively Score Severity of Rodent Cardiomyopathy.
- Published in:
- Toxicologic Pathology, 2021, v. 49, n. 4, p. 888, doi. 10.1177/0192623320972614
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- Publication type:
- Article
Deep Learning–Based Detection of Endothelial Tip Cells in the Oxygen-Induced Retinopathy Model.
- Published in:
- Toxicologic Pathology, 2021, v. 49, n. 4, p. 862, doi. 10.1177/0192623320972964
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- Publication type:
- Article
Artificial Intelligence in Toxicologic Pathology: Quantitative Evaluation of Compound-Induced Hepatocellular Hypertrophy in Rats.
- Published in:
- Toxicologic Pathology, 2021, v. 49, n. 4, p. 928, doi. 10.1177/0192623320983244
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- Publication type:
- Article
Screening For Bone Marrow Cellularity Changes in Cynomolgus Macaques in Toxicology Safety Studies Using Artificial Intelligence Models.
- Published in:
- Toxicologic Pathology, 2021, v. 49, n. 4, p. 905, doi. 10.1177/0192623320981560
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- Publication type:
- Article
Deep Learning in Toxicologic Pathology: A New Approach to Evaluate Rodent Retinal Atrophy.
- Published in:
- Toxicologic Pathology, 2021, v. 49, n. 4, p. 851, doi. 10.1177/0192623320980674
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- Publication type:
- Article
The Application, Challenges, and Advancement Toward Regulatory Acceptance of Digital Toxicologic Pathology: Results of the 7th ESTP International Expert Workshop (September 20-21, 2019).
- Published in:
- Toxicologic Pathology, 2021, v. 49, n. 4, p. 720, doi. 10.1177/0192623320975841
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- Publication type:
- Article
Developing a Qualification and Verification Strategy for Digital Tissue Image Analysis in Toxicological Pathology.
- Published in:
- Toxicologic Pathology, 2021, v. 49, n. 4, p. 773, doi. 10.1177/0192623320980310
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- Publication type:
- Article
Using Deep Learning Artificial Intelligence Algorithms to Verify N-Nitroso-N-Methylurea and Urethane Positive Control Proliferative Changes in Tg-RasH2 Mouse Carcinogenicity Studies.
- Published in:
- Toxicologic Pathology, 2021, v. 49, n. 4, p. 938, doi. 10.1177/0192623320973986
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- Publication type:
- Article
Digital 3D Topographic Microscopy: Bridging the Gaps Between Macroscopy, Microscopy and Scanning Electron Microscopy.
- Published in:
- Toxicologic Pathology, 2021, v. 49, n. 4, p. 963, doi. 10.1177/0192623320979908
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- Publication type:
- Article
Impact of Preanalytical Factors During Histology Processing on Section Suitability for Digital Image Analysis.
- Published in:
- Toxicologic Pathology, 2021, v. 49, n. 4, p. 755, doi. 10.1177/0192623320970534
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- Publication type:
- Article
Deep Learning-Based Spermatogenic Staging Assessment for Hematoxylin and Eosin-Stained Sections of Rat Testes.
- Published in:
- Toxicologic Pathology, 2021, v. 49, n. 4, p. 872, doi. 10.1177/0192623320969678
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- Publication type:
- Article
A Workflow for the Performance of the Differential Ovarian Follicle Count Using Deep Neuronal Networks.
- Published in:
- Toxicologic Pathology, 2021, v. 49, n. 4, p. 843, doi. 10.1177/0192623320969130
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- Publication type:
- Article
DICOM Format and Protocol Standardization—A Core Requirement for Digital Pathology Success.
- Published in:
- Toxicologic Pathology, 2021, v. 49, n. 4, p. 738, doi. 10.1177/0192623320965893
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- Publication type:
- Article
Letter to the Editor Regarding "Pathology Informatics Education Committee of the American College of Veterinary Pathologists (ACVP)".
- Published in:
- 2021
- By:
- Publication type:
- Editorial
Artificial Intelligence-Based Quantification of Epithelial Proliferation in Mammary Glands of Rats and Oviducts of Göttingen Minipigs.
- Published in:
- Toxicologic Pathology, 2021, v. 49, n. 4, p. 912, doi. 10.1177/0192623320950633
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- Publication type:
- Article