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Combining population and patient-specific characteristics for prostate segmentation on 3D CT images

Ling Ma, Rongrong Guo, Zhiqiang Tian, Rajesh Venkataraman, Saradwata Sarkar, Xiabi Liu, Funmilayo Tade, David M. Schuster, Baowei Fei, Martin A. Styner, Elsa D. Angelini
2016 Medical Imaging 2016: Image Processing  
Prostate segmentation on CT images is a challenging task. In this paper, we explore the population and patient-specific characteristics for the segmentation of the prostate on CT images.  ...  Because population learning does not consider the inter-patient variations and because patient-specific learning may not perform well for different patients, we are combining the population and patient-specific  ...  Specifically, we compute the similarity between the population and patient-specific models to combine the population and patient-specific characteristics for more accurate segmentation.  ... 
doi:10.1117/12.2216255 pmid:27660382 pmcid:PMC5029417 dblp:conf/miip/MaGTVSLTSF16 fatcat:qbemxt4t4zcwfjpkqybsbmkboy

Fully Automated Organ Segmentation in Male Pelvic CT Images [article]

Anjali Balagopal, Samaneh Kazemifar, Dan Nguyen, Mu-Han Lin, Raquibul Hannan, Amir Owrangi, Steve Jiang
2018 arXiv   pre-print
The models were trained and tested on a pelvic CT image dataset comprising 136 patients.  ...  We present a fully automated workflow for male pelvic CT image segmentation using deep learning.  ...  Ma et al. 23 proposed a combination of population-based and patient-based learning methods for segmenting the prostate on CT images.  ... 
arXiv:1805.12526v1 fatcat:bmfkx4zx3jclrewnlagnzjfpta

PO-0868: Optimal atlas size within OnQ rtsô for automated contouring of head and neck anatomical structures

C. Antoine, G. Webster, M. Tiffany, N. Nundlall, R. Simmons, A. Hartley
2013 Radiotherapy and Oncology  
Therefore, it is necessary to construct a method for accurate 3D quantification of NIR error.  ...  Our proposed method, which measures the distance and the direction of difference between reference and deformed contours, might be an effective method for evaluating NIR algorithms.  ...  For each clinical case, coregistered CT and 3DUS image datasets were available. Each patient was manually segmented by a qualified clinician on the fusion dataset.  ... 
doi:10.1016/s0167-8140(15)33174-1 fatcat:bqwfeeqr3jdz3jtcio5qbwnxuq

PO-0869: Automated cross-modal 3D contouring algorithm for prostate 3D ultrasound-CT co-registered images

D. Ermacora, S. Pesente, F. Pascoli, S. Raducci, R. Mauro, I. Abu Rumeileh, F. Verhaegen, D. Fontanarosa
2013 Radiotherapy and Oncology  
Therefore, it is necessary to construct a method for accurate 3D quantification of NIR error.  ...  Our proposed method, which measures the distance and the direction of difference between reference and deformed contours, might be an effective method for evaluating NIR algorithms.  ...  For each clinical case, coregistered CT and 3DUS image datasets were available. Each patient was manually segmented by a qualified clinician on the fusion dataset.  ... 
doi:10.1016/s0167-8140(15)33175-3 fatcat:lzbbsinzvjbbjpoluqsqru4744

Online updating of context-aware landmark detectors for prostate localization in daily treatment CT images

Xiubin Dai, Yaozong Gao, Dinggang Shen
2015 Medical Physics (Lancaster)  
To this end, the authors propose an online update scheme for landmarkguided prostate segmentation, which can fully exploit valuable patient-specific information contained in the previous treatment images  ...  Results: The experimental results on 330 images of 24 patients show the effectiveness of the authors' proposed online update scheme in improving the accuracies of both landmark detection and prostate segmentation  ...  In spite of high accuracy in CT prostate segmentation, the classification based methods require a sufficient number of manually segmented patient-specific images (i.e., at least three images) for training  ... 
doi:10.1118/1.4918755 pmid:25979051 pmcid:PMC4409630 fatcat:zqo6vhzn7rghdeht6zmwsr4czm

Automatic Segmentation of Pelvic Cancers Using Deep Learning: State-of-the-Art Approaches and Challenges

Reza Kalantar, Gigin Lin, Jessica M. Winfield, Christina Messiou, Susan Lalondrelle, Matthew D. Blackledge, Dow-Mu Koh
2021 Diagnostics  
and rectal cancers on computed tomography (CT) and magnetic resonance imaging (MRI), highlighting the key findings, challenges and limitations.  ...  This review provides a comprehensive, non-systematic and clinically-oriented overview of 74 DL-based segmentation studies, published between January 2016 and December 2020, for bladder, prostate, cervical  ...  From the 40 reviewed MRI-based prostate segmentation publications, 32 and 4 used 2D and 3D imaging data for training their DL networks, respectively, whilst one study used a combination of 2D and 3D input  ... 
doi:10.3390/diagnostics11111964 pmid:34829310 pmcid:PMC8625809 fatcat:alr36jtq6fgeddnluclp5neb2i

PO-0867: Novel evaluation method of non-rigid image registration algorithms for image-guided adapted radiation therapy

Y. Saito, K. Tateoka, T. Nakazawa, T. Abe, A. Nakata, M. Yano, K. Fujimoto, Y. Yaegashi, K. Shima, K. Sakata
2013 Radiotherapy and Oncology  
Materials and Methods: The simulation computed tomography (sim-CT) and CBCT images of an electron density phantom and 5 prostate cancer patients were acquired.  ...  The histograms of pixel values for each slice of the sim-CT and CBCT images of the electron density phantom and of the prostatic cancer patients were obtained with an in-house program.  ...  For each clinical case, coregistered CT and 3DUS image datasets were available. Each patient was manually segmented by a qualified clinician on the fusion dataset.  ... 
doi:10.1016/s0167-8140(15)33173-x fatcat:nfujlzjhjnawrn4h35miqodlsu

Assessment of Skeletal Tumor Load in Metastasized Castration-Resistant Prostate Cancer Patients: A Review of Available Methods and an Overview on Future Perspectives

Francesco Fiz, Helmut Dittman, Cristina Campi, Silvia Morbelli, Cecilia Marini, Massimo Brignone, Matteo Bauckneht, Roberta Piva, Anna Massone, Michele Piana, Gianmario Sambuceti, Christian la Fougère
2018 Bioengineering  
Studies could be categorized in the following categories: automated analysis of 2D scans, SUV-based thresholding, hybrid CT- and SUV-based thresholding, and MRI-based thresholding.  ...  For this reason, many computational approaches have been developed in the last decades to quantify the skeletal tumor burden and treatment response.  ...  For the purpose of the current review, we sorted these approaches in four different categories: 2D bone scan segmentation, 3D segmentation based on SUV threshold, 3D segmentation based on CT data or on  ... 
doi:10.3390/bioengineering5030058 pmid:30060546 fatcat:eelcsitxmzdlxctavdk44vcd44

Locally-constrained boundary regression for segmentation of prostate and rectum in the planning CT images

Yeqin Shao, Yaozong Gao, Qian Wang, Xin Yang, Dinggang Shen
2015 Medical Image Analysis  
Our method is evaluated on a planning CT image dataset with 70 images from 70 different patients.  ...  Automatic and accurate segmentation of the prostate and rectum in planning CT images is a challenging task due to low image contrast, unpredictable organ (relative) position, and uncertain existence of  ...  [6] leveraged both population and patient-specific image information for prostate deformable segmentation. Liao et al. [7] and Li et al.  ... 
doi:10.1016/j.media.2015.06.007 pmid:26439938 pmcid:PMC4679541 fatcat:u2q5cgjnozbxvm7iewo7ai7244

Comparison of 68Ga-HBED-CC PSMA-PET/CT and multiparametric MRI for gross tumour volume detection in patients with primary prostate cancer based on slice by slice comparison with histopathology

Constantinos Zamboglou, Vanessa Drendel, Cordula A. Jilg, Hans C. Rischke, Teresa I. Beck, Wolfgang Schultze-Seemann, Tobias Krauss, Michael Mix, Florian Schiller, Ulrich Wetterauer, Martin Werner, Mathias Langer (+3 others)
2017 Theranostics  
In each in-vivo CT slice the prostate was separated into 4 equal segments and sensitivity and specificity for PSMA PET and mpMRI were assessed by comparison with histological reference material.  ...  Resected prostates were scanned by ex-vivo CT in a special localizer and prepared for histopathology.  ...  Nanko and his team for the construction of the localizer and the cutting advice. We would like to thank C. Nolden for his skillful support for spelling and grammar.  ... 
doi:10.7150/thno.16638 pmid:28042330 pmcid:PMC5196899 fatcat:4cp2dj26gbcgvgwljxnbgl7ocq

68Ga-PSMA-PET/CT for the evaluation of pulmonary metastases and opacities in patients with prostate cancer

Jonathan Damjanovic, Jan-Carlo Janssen, Christian Furth, Gerd Diederichs, Thula Walter, Holger Amthauer, Marcus R. Makowski
2018 Cancer Imaging  
Methods: 68 Ga-PSMA-PET/CT scans of 739 PC patients available in our database were evaluated retrospectively for lung metastases and non-solid focal pulmonary opacities.  ...  The purpose of this study was to investigate the imaging properties of pulmonary metastases and benign opacities in 68 Ga-PSMA positron emission tomography (PET) in patients with prostate cancer (PC).  ...  Summary of the patients' characteristics, including age, PSA, GS and previous therapy. GS Gleason score, PSA prostate-specific antigen.  ... 
doi:10.1186/s40644-018-0154-8 pmid:29769114 pmcid:PMC5956855 fatcat:ut5ymyklcjg3blov5m6f23dhpi

A diffusion-weighted imaging based diagnostic system for early detection of prostate cancer

Ahmad Firjani, Ahmed Elnakib, Fahmi Khalifa, Georgy Gimel'farb, Mohamed Abou El-Ghar, Adel Elmaghraby, Ayman El-Baz
2013 Journal of Biomedical Science and Engineering  
A new framework for early diagnosis of prostate cancer using Diffusion-Weighted Imaging (DWI) is proposed.  ...  structures based on a Maximum A Posteriori (MAP) estimate of a new log-likelihood function that accounts for the shape priori, the spatial interaction, and the current appearance of prostate tissues and  ...  However, it has poor softtissue contrast resolution that does not allow precise distinction of the internal or external anatomy of the prostate and thus CT images have shown limited specificity for prostate  ... 
doi:10.4236/jbise.2013.63a044 fatcat:dtiq7lshs5d3vkm3ipoyehoy2m

Front Matter: Volume 9784

2016 Medical Imaging 2016: Image Processing  
[9784-21] 9784 0N A novel structured dictionary for fast processing of 3D medical images, with application to computed tomography restoration and denoising [9784-22] SESSION 6 SHAPE 9784 0P Landmark based  ...  Combining multi-atlas segmentation with brain surface estimation [9784-13] 9784 0F Automated segmentation of upper digestive tract from abdominal contrast-enhanced CT data using hierarchical statistical  ...  techniques evaluation based on a single compact breast mass classification scheme [9784-77] 9784 27 Combining population and patient-specific characteristics for prostate segmentation on 3D CT images  ... 
doi:10.1117/12.2240619 fatcat:kot6cogf4rf6dcjhkzdrr5gahi

Image-guided intensity-modulated radiotherapy of prostate cancer

Volker Rudat, A. Nour, M. Hammoud, A. Alaradi, A. Mohammed
2015 Strahlentherapie und Onkologie (Print)  
Overall population mean set-up error, S Population systematic error, s Population random error. a Safety margin to accommodate for the combined error of patient setup accuracy and prostate motion using  ...  In one patient a fiducial prostate marker migration was observed between the CT simulation and the first radiotherapy fraction.  ... 
doi:10.1007/s00066-015-0919-y pmid:26545764 pmcid:PMC4718949 fatcat:uokljjkssndwfmx4djybvsmjei

A Comparison of US- Versus MR-Based 3-D Prostate Shapes Using Radial Basis Function Interpolation and Statistical Shape Models

Ran Tao, Mahdi Tavakoli, Ron Sloboda, Nawaid Usmani
2015 IEEE journal of biomedical and health informatics  
This paper presents a comparison of 3D segmentations of the prostate, based on 2D manually-segmented contours, obtained using ultrasound (US) and magnetic resonance (MR) imaging data collected from 40  ...  patients diagnosed with localized prostate cancer and scheduled to receive brachytherapy treatment.  ...  For instance, in [17] , a cardiac left ventricle SSM model was built based on MR images with superior tissue definition and then used for contour segmentation in CT images without the need to re-train  ... 
doi:10.1109/jbhi.2014.2324975 pmid:24860042 fatcat:dqwm7qyonrcfdokadp3utxviwq
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