Supervised and Interactive Image Segmentation Techniques with an Application to Prostrate Cancer PDF Download
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Author: Yusuf Oguzhan Artan
Publisher:
ISBN:
Category :
Languages : en
Pages : 248
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Book Description
Author: Yusuf Oguzhan Artan
Publisher:
ISBN:
Category :
Languages : en
Pages : 248
Get Book Here
Book Description
Author: Anant Madabhushi
Publisher: Springer
ISBN: 3642239447
Category : Computers
Languages : en
Pages : 168
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Book Description
This book constitutes the refereed proceedings of the International Workshop on Prostate Cancer Imaging, held in conjunction with MICCAI 2011, in Toronto, Canada, in September 2011. The 15 revised full papers presented together with 2 invited talks were carefully reviewed and selected from 19 submissions. The papers cover the clinical areas of radiology, radiation oncology, and image guided intervention, addressing topics such as prostate segmentation, multi-modal prostate registration, and computer-aided diagnosis and classification of prostate cancer.
Author: Sachin Meena
Publisher:
ISBN:
Category :
Languages : en
Pages : 121
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Book Description
Over the past two decades interactive methods for clinical and biomedical image segmentation have been investigated since the pioneering work of Live-Wire, Live-Lane [17] and Intelligent Scissors [1]. Fully automatic image segmentation is essential for quantitative analysis but remains an unsolved problem, so user driven interactive methods continue to be a powerful alternative when extremely precise segmentation is required. However, manual methods although routinely used are tedious, time-consuming, expensive, inconsistent between experts and error prone. In semi-supervised interactive segmentation the goal is for the user to provide a small amount of partial information or hints for an automatic algorithm to use in order to produce accurate boundaries suitable for the user. The coupled interaction between the user provided input and the semi-supervised segmentation algorithm should be minimal and robust. Commonly used drawing tools for interactive segmentation interfaces include active contour or boundary drawing, scribbles to identify foreground and background regions, and rectangles to outline the object of interest. But interactive segmentation using a sparse set of seed-points has not been widely investigated. In this work we investigate the use of sparse seed point-based for interactive image segmentation task. We have also proposed a new regression based framework, making use of Elastic Body Splines (EBS) to perform interactive image segmentation. Elastic Body Splines belonging to the family of 3D splines were recently introduced to capture tissue deformations within a physical model-based approach for non-rigid biomedical image registration [18]. ElasticMap model the displacement of points in a 3D homogeneous isotropic elastic body subject to forces. We propose a novel extension of using elastic body splines for interactive learning-based figure-ground segmentation. The task of interactive image segmentation, with user provided foreground-background labeled seeds or samples, is formulated as learning a spatially dependent interpolating pixel classification function that is then used to assign labels for all unlabeled pixels in the image. The spline function we chose to model the semisupervised pixel classifier is the ElasticMap which can use sparse point-scribble input from the user and has a closed form solution. Experimental results demonstrate the applicability of the EBS approach for image segmentation. The ElasticMap method for interactive foreground segmentation uses on an average just four to six labeled pixels as input from the user. Using such sparsely labeled information the proposed EBS method produces very accurate results with an average accuracy consistently exceeding 95 percent on three different benchmark datasets and outperforms eleven other popular interactive image segmentation methods.
Author: Robert L. Bard
Publisher: Springer Science & Business Media
ISBN: 3642404294
Category : Medical
Languages : en
Pages : 269
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Book Description
Image-Guided Prostate Cancer Treatments is a comprehensive reference and practical guide on the technology and application of ultrasound and MRI in the male pelvis, with special attention to the prostate. The book is organized into three main sections, the first of which is devoted to general aspects of imaging and image-guided treatments. The second section provides a systematic overview of the application of ultrasound and MRI to the diagnosis and treatment of diseases of the lower urinary tract. Performance of the ultrasound and MRI studies is explained, and the normal and abnormal pathological anatomy is reviewed. Correlation with the ultrasound in the same plane is provided to assist in understanding the MRI sequences. Biopsy and interventional procedures, ultrasound-MRI fusion techniques, and image-guided therapies, including focused ultrasound, photodynamic therapy, microwave and laser ablation, are all fully covered. The third section focuses on securing treatment effectiveness and the use of follow-up imaging to ensure therapeutic success and detect tumor recurrence at an early stage, which is vital given that prompt focal treatment of recurrence is very successful. Here, particular attention is paid to the role of Doppler ultrasound and DCE-MRI technologies. This book, containing a wealth of high-quality illustrations based on high-end equipment, will acquaint beginners with the basics of prostate ultrasound and MRI, while more advanced practitioners will learn new skills, means of avoiding pitfalls, and ways of effectively relating the imaging and image-guided treatments to the clinical situation. The information provided will permit a tailored approach in dealing with specific pathologic issues.
Author: Ayman El-Baz
Publisher: CRC Press
ISBN: 0429784678
Category : Technology & Engineering
Languages : en
Pages : 363
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Book Description
This book covers novel strategies and state of the art approaches for automated non-invasive systems for early prostate cancer diagnosis. Prostate cancer is the most frequently diagnosed malignancy after skin cancer and the second leading cause of cancer related male deaths in the USA after lung cancer. However, early detection of prostate cancer increases chances of patients’ survival. Generally, The CAD systems analyze the prostate images in three steps: (i) prostate segmentation; (ii) Prostate description or feature extraction; and (iii) classification of the prostate status. Explores all of the latest research and developments in state-of-the art imaging of the prostate from world class experts. Contains a comprehensive overview of 2D/3D Shape Modeling for MRI data. Presents a detailed examination of automated segmentation of the prostate in 3D imaging. Examines Computer-Aided-Diagnosis through automated techniques. There will be extensive references at the end of each chapter to enhance further study.
Author: A.Pasumpon Pandian
Publisher: Springer Nature
ISBN: 9811609659
Category : Technology & Engineering
Languages : en
Pages : 980
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Book Description
This book presents best selected research papers presented at the International Conference on Computer Networks, Big Data and IoT (ICCBI 2020), organized by Vaigai College Engineering, Madurai, Tamil Nadu, India, during 15–16 December 2020. The book covers original papers on computer networks, network protocols and wireless networks, data communication technologies and network security. The book is a valuable resource and reference for researchers, instructors, students, scientists, engineers, managers and industry practitioners in those important areas.
Author: Guorong Wu
Publisher: Springer
ISBN: 3319105817
Category : Computers
Languages : en
Pages : 343
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Book Description
This book constitutes the refereed proceedings of the 5th International Workshop on Machine Learning in Medical Imaging, MLMI 2014, held in conjunction with the International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2014, in Cambridge, MA, USA, in September 2014. The 40 contributions included in this volume were carefully reviewed and selected from 70 submissions. They focus on major trends and challenges in the area of machine learning in medical imaging and aim to identify new cutting-edge techniques and their use in medical imaging.
Author: Ayman S. El-Baz
Publisher: Springer Science & Business Media
ISBN: 1441982043
Category : Medical
Languages : en
Pages : 369
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Book Description
With the advances in image guided surgery for cancer treatment, the role of image segmentation and registration has become very critical. The central engine of any image guided surgery product is its ability to quantify the organ or segment the organ whether it is a magnetic resonance imaging (MRI) and computed tomography (CT), X-ray, PET, SPECT, Ultrasound, and Molecular imaging modality. Sophisticated segmentation algorithms can help the physicians delineate better the anatomical structures present in the input images, enhance the accuracy of medical diagnosis and facilitate the best treatment planning system designs. The focus of this book in towards the state of the art techniques in the area of image segmentation and registration.
Author: Anant Madabhushi
Publisher: Springer
ISBN: 3642159893
Category : Computers
Languages : en
Pages : 153
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Book Description
Prostatic adenocarcinoma (CAP) is the second most common malignancy with an estimated 190,000 new cases in the USA in 2010 (Source: American Cancer Society), and is the most frequently diagnosed cancer among men. If CAP is caught early, men have a high, five-year survival rate. Unfortunately there is no standardized ima- based screening protocol for early detection of CAP (unlike for breast cancers). In the USA high levels of prostate-specific antigen (PSA) warrant a trans-rectal ultrasound (TRUS) biopsy to enable histologic confirmation of presence or absence of CAP. With recent rapid developments in multi-parametric radiological imaging te- niques (spectroscopy, dynamic contrast enhanced MR imaging, PET, RF ultrasound), some of these functional and metabolic imaging modalities are allowing for definition of high resolution, multi-modal signatures for prostate cancer in vivo. Distinct com- tational and technological challenges for multi-modal data registration and classifi- tion still remain in leveraging this multi-parametric data for directing therapy and optimizing biopsy. Additionally, with the recent advent of whole slide digital sc- ners, digitized histopathology has become amenable to computerized image analysis. While it is known that outcome of prostate cancer (prognosis) is highly correlated with Gleason grade, pathologists often have difficulty in distinguishing between interme- ate Gleason grades from histopathology. Development of computerized image analysis methods for automated Gleason grading and predicting outcome on histopathology have to confront the significant computational challenges associated with working these very large digitized images.
Author: John Bukowy
Publisher:
ISBN:
Category :
Languages : en
Pages : 124
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Book Description
