Author

Maria Thor

Memorial Sloan Kettering Cancer Center

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Bioinformatics· 2

Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Assay:imaging· 2 Research Focus:clustering· 1 Organism:human· 1 Research Focus:software / tool· 1

Frequent Co-Authors

Aditi IyeriD· 2 shared Aditya ApteiD· 2 shared Harini VeeraraghavaniD· 2 shared Joseph O. DeasyiD· 2 shared Sharif ElguindiiD· 2 shared Amita Shukla‐DaveiD· 1 shared Andy Jackson· 1 shared Eve LoCastroiD· 1 shared

Activity by Year

2019-2021 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 39 mutual co-author links

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2 shared papersBioinformatics

Aditi IyerORCID

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2 papers

Recent·Most cited

Deep learning-based auto-segmentation of swallowing and chewing structures

Aditi Iyer, Maria Thor, Ifeanyirochukwu Onochie, Jennifer Hesse, Kaveh Zakeri, Eve LoCastro, Jue Jiang, Harini Veeraraghavan, Sharif Elguindi, Nancy Y. Lee, Joseph O. Deasy, Aditya Apte

This paper develops deep learning models to automate segmentation of swallowing and chewing structures in H&N CT scans, achieving high accuracy and clinical utility.

Physics in Medicine and Biology · Dec 7, 2021Peer-reviewedBioinformatics

Library of model implementations for sharing deep-learning image segmentation and outcomes models

Aditya Apte, Aditi Iyer, Maria Thor, Rutu Pandya, Rabia Haq, Amita Shukla‐Dave, Hu Yu-Chi, Sharif Elguindi, Harini Veeraraghavan, Jung Hun Oh, Andy Jackson, Joseph O. Deasy

The paper presents an open-source library of deep-learning models for image segmentation and outcomes in oncology, enabling validation, automation, and integration into clinical workflows.

bioRxiv · Sep 19, 2019 · PreprintBioinformatics