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Instance-Based Vision Transformer for Subtyping of Papillary Renal Cell Carcinoma in Histopathological Image

https://doi.org/10.1007/978-3-030-87237-3_29
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Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-3-030-17938-0_19openalex-snapshot
Classifying Breast Cancer Histopathological Images Using a Robust Artificial Neural Network Architecture
inferredcites →https://doi.org/10.1007/978-3-030-59722-1_42openalex-snapshot
Renal Cell Carcinoma Detection and Subtyping with Minimal Point-Based Annotation in Whole-Slide Images
inferredcites →https://doi.org/10.1007/978-3-030-87237-3_13openalex-snapshot
Nuclei Grading of Clear Cell Renal Cell Carcinoma in Histopathological Image by Composite High-Resolution Network
inferredcites →https://doi.org/10.1016/j.ejca.2012.05.002openalex-snapshot
Incidence and long-term prognosis of papillary compared to clear cell renal cell carcinoma – A multicentre study
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The 2016 WHO Classification of Tumours of the Urinary System and Male Genital Organs—Part A: Renal, Penile, and Testicular Tumours
inferredcites →https://doi.org/10.1016/j.media.2018.12.003openalex-snapshot
Micro-Net: A unified model for segmentation of various objects in microscopy images
inferredcites →https://doi.org/10.1016/j.media.2019.101563openalex-snapshot
Hover-Net: Simultaneous segmentation and classification of nuclei in multi-tissue histology images
inferredcites →https://doi.org/10.1016/j.urolonc.2019.05.009openalex-snapshot
Morphologic subtyping as a prognostic predictor for survival in papillary renal cell carcinoma: Type 1 vs. type 2
inferredcites →https://doi.org/10.1038/s41591-018-0177-5openalex-snapshot
Classification and mutation prediction from non–small cell lung cancer histopathology images using deep learning
inferredcites →https://doi.org/10.1038/s41598-020-65262-zopenalex-snapshot
In vitro evaluation of Penicillium chrysogenum Snef1216 against Meloidogyne incognita (root-knot nematode)
inferredcites →https://doi.org/10.1038/s41598-020-78174-9openalex-snapshot
The effect of the papillary renal cell carcinoma subtype on oncological outcomes
inferredcites →https://doi.org/10.1097/01.mp.0000036346.88874.25openalex-snapshot
Morphologic Subtyping of Papillary Renal Cell Carcinoma: Correlation with Prognosis and Differential Expression of MUC1 between the Two Subtypes
inferredcites →https://doi.org/10.1097/pas.0b013e318299f0fbopenalex-snapshot
The International Society of Urological Pathology (ISUP) Grading System for Renal Cell Carcinoma and Other Prognostic Parameters
inferredcites →https://doi.org/10.1109/icdm50108.2020.00094openalex-snapshot
Rethinking Dice Loss for Medical Image Segmentation
inferredcites →https://doi.org/10.1109/isbi48211.2021.9433794openalex-snapshot
Recist-Net: Lesion Detection Via Grouping Keypoints On Recist-Based Annotation
inferredcites →https://doi.org/10.1158/0008-5472.can-17-0313openalex-snapshot
Integrative Analysis of Histopathological Images and Genomic Data Predicts Clear Cell Renal Cell Carcinoma Prognosis
inferredcites →https://doi.org/10.1158/0008-5472.can-19-1629openalex-snapshot
Computational Staining of Pathology Images to Study the Tumor Microenvironment in Lung Cancer
inferredcites →https://doi.org/10.13140/rg.2.2.12290.02244/1openalex-snapshot
Multi-organ Nuclei Segmentation and Classification Challenge 2020
inferredcites →https://doi.org/10.48550/arxiv.2010.11929openalex-snapshot
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
inferredcites →https://doi.org/10.65215/2q58a426openalex-snapshot
Attention Is All You Need

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