AIMC Topic: Tissue Fixation

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Exploratory multi-cohort, multi-reader study on the clinical utility of a deep learning model for transforming cryosectioned to formalin-fixed, paraffin-embedded (FFPE) images in breast lesion diagnosis.

Breast cancer research : BCR Jun 17, 2025
BACKGROUND: Cryosectioned tissues often exhibit artifacts that compromise pathologists' diagnostic accuracy during intraoperative assessments. These inconsistencies, compounded by variations in frozen section (FS) production across laboratories, high...
Breast Image Interpretation, Computer-Assisted Image Processing, Computer-Assisted Formaldehyde Paraffin Embedding Cryoultramicrotomy Tissue Fixation Frozen Sections Female Breast Neoplasms Deep Learning Cohort Studies Humans
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Multiview confocal super-resolution microscopy.

Nature Nov 26, 2021
Confocal microscopy remains a major workhorse in biomedical optical microscopy owing to its reliability and flexibility in imaging various samples, but suffers from substantial point spread function anisotropy, diffraction-limited resolution, depth-d...
Single-Cell Analysis Mice Deep Learning Cell Line, Tumor Organ Specificity Drosophila melanogaster Microscopy, Confocal Myoblasts Humans Animals Imaginal Discs Caenorhabditis elegans Tissue Fixation
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Diagnosis of T-cell-mediated kidney rejection in formalin-fixed, paraffin-embedded tissues using RNA-Seq-based machine learning algorithms.

Human pathology Oct 6, 2018
Molecular diagnosis is being increasingly used in transplant pathology to render more objective and quantitative determinations that also provide mechanistic and prognostic insights. This study performed RNA-Seq on biopsies from kidneys with stable f...
Tissue Fixation Paraffin Embedding Graft Rejection Formaldehyde Sequence Analysis, RNA Humans Machine Learning Algorithms Adult T-Lymphocytes Male Middle Aged Aged Young Adult Kidney Transplantation Female
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Machine Learning-based Classification of Diffuse Large B-cell Lymphoma Patients by Their Protein Expression Profiles.

Molecular & cellular proteomics : MCP Aug 26, 2015
Characterization of tumors at the molecular level has improved our knowledge of cancer causation and progression. Proteomic analysis of their signaling pathways promises to enhance our understanding of cancer aberrations at the functional level, but ...
Tissue Fixation Phosphoprotein Phosphatases Tissue Embedding Neprilysin Neoplasm Proteins Principal Component Analysis Isotope Labeling Lymphoma, Large B-Cell, Diffuse Proteome GTPase-Activating Proteins Cell Line, Tumor Machine Learning Gene Expression Regulation, Neoplastic Signal Transduction Formaldehyde Humans Biomarkers, Tumor Apoptosis Regulatory Proteins Proteomics
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