@inproceedings{bcd147cbe07649d08f7ba08602a8ad5f,
title = "A Bi-directional, Multi-modality Framework for Segmentation of Brain Structures",
abstract = "Careful delineation of normal-tissue organs-at-risk is essential for brain tumor radiotherapy. However, this process is time-consuming and subject to variability. In this work, we propose a multi-modality framework that automatically segments eleven structures. Large structures used for defining the clinical target volume (CTV), such as the cerebellum, are directly segmented from T1-weighted and T2-weighted MR images. Smaller structures used in radiotherapy plan optimization are more difficult to segment, thus, a region of interest is first identified and cropped by a classification model, and then these structures are segmented from the new volume. This bi-directional framework allows for rapid model segmentation and good performance on a standardized challenge dataset when evaluated with volumetric and surface metrics.",
keywords = "ABCs, Deep learning, MICCAI 2020, Segmentation",
author = "Gay, {Skylar S.} and Cenji Yu and Rhee, {Dong Joo} and Carlos Sjogreen and Mumme, {Raymond P.} and Nguyen, {Callistus M.} and Netherton, {Tucker J.} and Cardenas, {Carlos E.} and Court, {Laurence E.}",
note = "Publisher Copyright: {\textcopyright} 2021, Springer Nature Switzerland AG.; Anatomical Brain Barriers to Cancer Spread: Segmentation from CT and MR Images Challenge, ABCs 2020, Learn2Reg Challenge, L2R 2020 and Thyroid Nodule Segmentation and Classification in Ultrasound Images Challenge, TN-SCUI 2020 held in conjunction with 23rd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2020 ; Conference date: 04-10-2020 Through 08-10-2020",
year = "2021",
doi = "10.1007/978-3-030-71827-5_6",
language = "English (US)",
isbn = "9783030718268",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "49--57",
editor = "Nadya Shusharina and Heinrich, {Mattias P.} and Ruobing Huang",
booktitle = "Segmentation, Classification, and Registration of Multi-modality Medical Imaging Data - MICCAI 2020 Challenges, ABCs 2020, L2R 2020, TN-SCUI 2020, Held in Conjunction with MICCAI 2020, Proceedings",
address = "Germany",
}