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Jiang J, Guo Y, Bi Z, Huang Z, Yu G, Wang J. Segmentation of prostate ultrasound images: the state of the art and the future directions of segmentation algorithms. Artif Intell Rev 2022. [DOI: 10.1007/s10462-022-10179-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2022]
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Ghose S, Denham JW, Ebert MA, Kennedy A, Mitra J, Dowling JA. Multi-atlas and unsupervised learning approach to perirectal space segmentation in CT images. AUSTRALASIAN PHYSICAL & ENGINEERING SCIENCES IN MEDICINE 2016; 39:933-941. [PMID: 27844331 DOI: 10.1007/s13246-016-0496-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/18/2016] [Accepted: 10/31/2016] [Indexed: 11/27/2022]
Abstract
Perirectal space segmentation in computed tomography images aids in quantifying radiation dose received by healthy tissues and toxicity during the course of radiation therapy treatment of the prostate. Radiation dose normalised by tissue volume facilitates predicting outcomes or possible harmful side effects of radiation therapy treatment. Manual segmentation of the perirectal space is time consuming and challenging in the presence of inter-patient anatomical variability and may suffer from inter- and intra-observer variabilities. However automatic or semi-automatic segmentation of the perirectal space in CT images is a challenging task due to inter patient anatomical variability, contrast variability and imaging artifacts. In the model presented here, a volume of interest is obtained in a multi-atlas based segmentation approach. Un-supervised learning in the volume of interest with a Gaussian-mixture-modeling based clustering approach is adopted to achieve a soft segmentation of the perirectal space. Probabilities from soft clustering are further refined by rigid registration of the multi-atlas mask in a probabilistic domain. A maximum a posteriori approach is adopted to achieve a binary segmentation from the refined probabilities. A mean volume similarity value of 97% and a mean surface difference of 3.06 ± 0.51 mm is achieved in a leave-one-patient-out validation framework with a subset of a clinical trial dataset. Qualitative results show a good approximation of the perirectal space volume compared to the ground truth.
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Affiliation(s)
- Soumya Ghose
- Department of Biomedical Engineering, Case Western Reserve University, 10900 Euclid Ave, Cleveland, OH, 44106, USA
| | - James W Denham
- School of Medicine and Public Health, University of Newcastle, Callaghan, NSW, 2308, Australia
| | - Martin A Ebert
- Radiation Oncology, Sir Charles Gairdner Hospital, Hospital Ave, Nedlands, WA, 6009, Australia. .,School of Physics, University of Western Australia, 35 Stirling Hwy, Crawley, WA, 6009, Australia.
| | - Angel Kennedy
- Radiation Oncology, Sir Charles Gairdner Hospital, Hospital Ave, Nedlands, WA, 6009, Australia
| | - Jhimli Mitra
- Department of Biomedical Engineering, Case Western Reserve University, 10900 Euclid Ave, Cleveland, OH, 44106, USA
| | - Jason A Dowling
- Australian e-Health Research Centre, CSIRO, Brisbane, QLD, 4029, Australia
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Chilali O, Ouzzane A, Diaf M, Betrouni N. A survey of prostate modeling for image analysis. Comput Biol Med 2014; 53:190-202. [PMID: 25156801 DOI: 10.1016/j.compbiomed.2014.07.019] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2013] [Revised: 06/22/2014] [Accepted: 07/23/2014] [Indexed: 11/18/2022]
Affiliation(s)
- O Chilali
- Inserm U703, 152, rue du Docteur Yersin, Lille University Hospital, 59120 Loos, France; Automatic Department, Mouloud Mammeri University, Tizi-Ouzou, Algeria
| | - A Ouzzane
- Inserm U703, 152, rue du Docteur Yersin, Lille University Hospital, 59120 Loos, France; Urology Department, Claude Huriez Hospital, Lille University Hospital, France
| | - M Diaf
- Automatic Department, Mouloud Mammeri University, Tizi-Ouzou, Algeria
| | - N Betrouni
- Inserm U703, 152, rue du Docteur Yersin, Lille University Hospital, 59120 Loos, France.
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