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Raudaschl PF, Zaffino P, Sharp GC, Spadea MF, Chen A, Dawant BM, Albrecht T, Gass T, Langguth C, Lüthi M, Jung F, Knapp O, Wesarg S, Mannion-Haworth R, Bowes M, Ashman A, Guillard G, Brett A, Vincent G, Orbes-Arteaga M, Cárdenas-Peña D, Castellanos-Dominguez G, Aghdasi N, Li Y, Berens A, Moe K, Hannaford B, Schubert R, Fritscher KD. Evaluation of segmentation methods on head and neck CT: Auto-segmentation challenge 2015. Med Phys 2017; 44:2020-2036. [PMID: 28273355 DOI: 10.1002/mp.12197] [Citation(s) in RCA: 136] [Impact Index Per Article: 19.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2016] [Revised: 10/13/2016] [Accepted: 02/22/2017] [Indexed: 01/28/2023] Open
Abstract
PURPOSE Automated delineation of structures and organs is a key step in medical imaging. However, due to the large number and diversity of structures and the large variety of segmentation algorithms, a consensus is lacking as to which automated segmentation method works best for certain applications. Segmentation challenges are a good approach for unbiased evaluation and comparison of segmentation algorithms. METHODS In this work, we describe and present the results of the Head and Neck Auto-Segmentation Challenge 2015, a satellite event at the Medical Image Computing and Computer Assisted Interventions (MICCAI) 2015 conference. Six teams participated in a challenge to segment nine structures in the head and neck region of CT images: brainstem, mandible, chiasm, bilateral optic nerves, bilateral parotid glands, and bilateral submandibular glands. RESULTS This paper presents the quantitative results of this challenge using multiple established error metrics and a well-defined ranking system. The strengths and weaknesses of the different auto-segmentation approaches are analyzed and discussed. CONCLUSIONS The Head and Neck Auto-Segmentation Challenge 2015 was a good opportunity to assess the current state-of-the-art in segmentation of organs at risk for radiotherapy treatment. Participating teams had the possibility to compare their approaches to other methods under unbiased and standardized circumstances. The results demonstrate a clear tendency toward more general purpose and fewer structure-specific segmentation algorithms.
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Affiliation(s)
- Patrik F Raudaschl
- Department of Biomedical Computer Science and Mechatronics, Institute for Biomedical Image Analysis, UMIT, Hall, Tyrol, 6060, Austria
| | - Paolo Zaffino
- Department of Experimental and Clinical Medicine, Magna Graecia University of Catanzaro, Catanzaro, 88100, Italy
| | - Gregory C Sharp
- Department of Radiation Oncology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114, USA
| | - Maria Francesca Spadea
- Department of Experimental and Clinical Medicine, Magna Graecia University of Catanzaro, Catanzaro, 88100, Italy
| | - Antong Chen
- Merck and Co., Inc., West Point, PA, 19422, USA
| | - Benoit M Dawant
- Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN, 37235, USA
| | | | - Tobias Gass
- Varian Medical Systems, Baden, 5404, Switzerland
| | | | | | | | | | | | | | - Mike Bowes
- Imorphics Ltd., Kilburn House, Manchester Science Park, Manchester, M15 6SE, UK
| | - Annaliese Ashman
- Imorphics Ltd., Kilburn House, Manchester Science Park, Manchester, M15 6SE, UK
| | - Gwenael Guillard
- Imorphics Ltd., Kilburn House, Manchester Science Park, Manchester, M15 6SE, UK
| | - Alan Brett
- Imorphics Ltd., Kilburn House, Manchester Science Park, Manchester, M15 6SE, UK
| | - Graham Vincent
- Imorphics Ltd., Kilburn House, Manchester Science Park, Manchester, M15 6SE, UK
| | | | - David Cárdenas-Peña
- Signal Processing and Recognition Group, Universidad Nacional de Colombia, Colombia
| | | | - Nava Aghdasi
- University of Washington, Seattle, WA, 98105, USA
| | - Yangming Li
- University of Washington, Seattle, WA, 98105, USA
| | | | - Kris Moe
- University of Washington, Seattle, WA, 98105, USA
| | | | - Rainer Schubert
- Department of Biomedical Computer Science and Mechatronics, Institute for Biomedical Image Analysis, UMIT, Hall, Tyrol, 6060, Austria
| | - Karl D Fritscher
- Department of Biomedical Computer Science and Mechatronics, Institute for Biomedical Image Analysis, UMIT, Hall, Tyrol, 6060, Austria
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