Learning-Based Multi-Label Segmentation of Transrectal Ultrasound Images for Prostate Brachytherapy

Segmentation of prostate boundaries in transrectal ultrasound (TRUS) images plays a great role in prostate cancer diagnosis. Due to the low signal to noise ratio and existence of the speckle noise in TRUS images, prostate image segmentation has proven to be an extremely difficult task. In this thesis report, a fast fully automated hybrid segmentation method based on probabilistic approaches is presented. First, the position of the initial model is automatically estimated using prostate boundary representative patterns. Next, the Expectation Maximization (EM) algorithm and Markov Random Field (MRF) theory are utilized in the deformation strategy to optimally fit the initial model on the prostate boundaries. A less computationally EM algorithm and a new surface smoothing technique are proposed to decrease the segmentation time. Successful experimental results with the average Dice Similarity Coefficient (DSC) value 93.9±2.7% and computational time around 9 seconds validate the algorithm.

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Impact of transrectal ultrasound- and computed tomography-based seed localization on postimplant dosimetry in prostate brachytherapy

Brachytherapy ◽

10.1016/j.brachy.2008.11.008 ◽

2009 ◽

Vol 8 (2) ◽

pp. 255-264 ◽

Cited By ~ 2

Author(s):

Meng-Sang Chew ◽

Jinyu Xue ◽

Chris Houser ◽

Vladimir Misic ◽

Junsheng Cao ◽

...

Keyword(s):

Computed Tomography ◽

Transrectal Ultrasound ◽

Prostate Brachytherapy ◽

Postimplant Dosimetry ◽

Seed Localization

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Texture Feature-Based Classification on Transrectal Ultrasound Image for Prostatic Cancer Detection

Computational and Mathematical Methods in Medicine ◽

10.1155/2020/7359375 ◽

2020 ◽

Vol 2020 ◽

pp. 1-9

Author(s):

Xiaofu Huang ◽

Ming Chen ◽

Peizhong Liu ◽

Yongzhao Du

Keyword(s):

Prostate Cancer ◽

Early Detection ◽

Markov Random Fields ◽

Transrectal Ultrasound ◽

Ultrasound Image ◽

Texture Features ◽

Svm Classifier ◽

Ultrasound Images ◽

Malignant Tumours ◽

Data Set

Prostate cancer is one of the most common cancers in men. Early detection of prostate cancer is the key to successful treatment. Ultrasound imaging is one of the most suitable methods for the early detection of prostate cancer. Although ultrasound images can show cancer lesions, subjective interpretation is not accurate. Therefore, this paper proposes a transrectal ultrasound image analysis method, aiming at characterizing prostate tissue through image processing to evaluate the possibility of malignant tumours. Firstly, the input image is preprocessed by optical density conversion. Then, local binarization and Gaussian Markov random fields are used to extract texture features, and the linear combination is performed. Finally, the fused texture features are provided to SVM classifier for classification. The method has been applied to data set of 342 transrectal ultrasound images obtained from hospitals with an accuracy of 70.93%, sensitivity of 70.00%, and specificity of 71.74%. The experimental results show that it is possible to distinguish cancerous tissues from noncancerous tissues to some extent.

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Pre-implant magnetic resonance and transrectal ultrasound imaging in high-dose-rate prostate brachytherapy: comparison of prostate volumes, craniocaudal extents, and contours

Journal of Contemporary Brachytherapy ◽

10.5114/jcb.2018.77947 ◽

2018 ◽

Vol 10 (4) ◽

pp. 285-290

Author(s):

Simone Grisotto ◽

Annamaria Cerrotta ◽

Brigida Pappalardi ◽

Mauro Carrara ◽

Antonella Messina ◽

...

Keyword(s):

Magnetic Resonance ◽

Dose Rate ◽

Ultrasound Imaging ◽

Transrectal Ultrasound ◽

High Dose Rate ◽

High Dose ◽

Prostate Brachytherapy

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Prostate Tissue Characterization/Classification in 144 Patient Population Using Wavelet and Higher Order Spectra Features from Transrectal Ultrasound Images

Technology in Cancer Research & Treatment ◽

10.7785/tcrt.2012.500346 ◽

2013 ◽

Vol 12 (6) ◽

pp. 545-557 ◽

Cited By ~ 18

Author(s):

Gyan Pareek ◽

U. Rajendra Acharya ◽

S. Vinitha Sree ◽

G. Swapna ◽

Ratna Yantri ◽

...

Keyword(s):

Patient Population ◽

Tissue Characterization ◽

Transrectal Ultrasound ◽

Higher Order ◽

Prostate Tissue ◽

Ultrasound Images ◽

Higher Order Spectra

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Systematic Review of Focal Prostate Brachytherapy and the Future Implementation of Image-Guided Prostate HDR Brachytherapy Using MR-Ultrasound Fusion

Prostate Cancer ◽

10.1155/2016/4754031 ◽

2016 ◽

Vol 2016 ◽

pp. 1-13 ◽

Cited By ~ 19

Author(s):

M. Sean Peach ◽

Daniel M. Trifiletti ◽

Bruce Libby

Keyword(s):

At Risk ◽

Organs At Risk ◽

Transrectal Ultrasound ◽

Prostate Brachytherapy ◽

Hdr Brachytherapy ◽

Clinical Papers ◽

Image Guided ◽

Focal Treatment ◽

Definitive Therapy

Prostate cancer is the most common malignancy found in North American and European men and the second most common cause of cancer related death. Since the practice of PSA screening has become common the disease is most often found early and can have a long indolent course. Current definitive therapy treats the whole gland but has considerable long-term side effects. Focal therapies may be able to target the cancer while decreasing dose to organs at risk. Our objective was to determine if focal prostate brachytherapy could meet target objectives while permitting a decrease in dose to organs at risk in a way that would allow future salvage treatments. Further, we wanted to determine if focal treatment results in less toxicity. Utilizing the Medline repository, dosimetric papers comparing whole gland to partial gland brachytherapy and clinical papers that reported toxicity of focal brachytherapy were selected. A total of 9 dosimetric and 6 clinical papers met these inclusion criteria. Together, these manuscripts suggest that focal brachytherapy may be employed to decrease dose to organs at risk with decreased toxicity. Of current technology, image-guided HDR brachytherapy using MRI registered to transrectal ultrasound offers the flexibility and efficiency to achieve such focal treatments.

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