Cross-Modality Brain Structures Image Segmentation for the Radiotherapy Target Definition and Plan Optimization
| Autor: | Brian De, Yufei Liu, Jonas Söderberg, Soleil Hernandez, Moaaz Soliman, Carlos E. Cardenas, Kevin Diao, Sean Maroongroge, Nadya Shusharina, Thomas Bortfeld |
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| Rok vydání: | 2021 |
| Předmět: |
Computer science
Tentorium cerebelli Optic chiasm Image segmentation Anatomy Fluid-attenuated inversion recovery medicine.disease Sagittal plane 030218 nuclear medicine & medical imaging Falx cerebri 03 medical and health sciences 0302 clinical medicine medicine.anatomical_structure 030220 oncology & carcinogenesis Glioma medicine Segmentation |
| Zdroj: | Segmentation, Classification, and Registration of Multi-modality Medical Imaging Data ISBN: 9783030718268 MICCAI (Challenges) |
| Popis: | This paper summarizes results of the International Challenge “Anatomical Brain Barriers to Cancer Spread: Segmentation from CT and MR Images”, ABCs, organized in conjunction with the MICCAI 2020 conference. Eighteen segmentation algorithms were trained on a set of 45 CT, T\(_1\)-weighted MR, and T\(_2\)-weighted FLAIR MR post-operative images of glioblastoma and low-grade glioma patients. Manual delineations were provided for the brain structures: falx cerebri, tentorium cerebelli, transverse and sagittal brain sinuses, ventricles, cerebellum (Task 1) and for the brainstem, structures of visual pathway, optic chiasm, optic nerves, and eyes, structures of auditory pathway, cochlea, and lacrimal glands (Task 2). The algorithms were tested on a set of 15 cases and received the final score for predicting segmentation on a separate 15 case image set. Multi-rater delineations with seven raters were obtained for the three cases. The results suggest that neural network based algorithms have become a successful technique of brain structure segmentation, and closely approach human performance in segmenting specific brain structures. |
| Databáze: | OpenAIRE |
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