Paper
5 March 2007 Comparative evaluation of a novel 3D segmentation algorithm on in-treatment radiotherapy cone beam CT images
Gareth Price, Chris Moore
Author Affiliations +
Abstract
Image segmentation and delineation is at the heart of modern radiotherapy, where the aim is to deliver as high a radiation dose as possible to a cancerous target whilst sparing the surrounding healthy tissues. This, of course, requires that a radiation oncologist dictates both where the tumour and any nearby critical organs are located. As well as in treatment planning, delineation is of vital importance in image guided radiotherapy (IGRT): organ motion studies demand that features across image databases are accurately segmented, whilst if on-line adaptive IGRT is to become a reality, speedy and correct target identification is a necessity. Recently, much work has been put into the development of automatic and semi-automatic segmentation tools, often using prior knowledge to constrain some grey level, or derivative thereof, interrogation algorithm. It is hoped that such techniques can be applied to organ at risk and tumour segmentation in radiotherapy. In this work, however, we make the assumption that grey levels do not necessarily determine a tumour's extent, especially in CT where the attenuation coefficient can often vary little between cancerous and normal tissue. In this context we present an algorithm that generates a discontinuity free delineation surface driven by user placed, evidence based support points. In regions of sparse user supplied information, prior knowledge, in the form of a statistical shape model, provides guidance. A small case study is used to illustrate the method. Multiple observers (between 3 and 7) used both the presented tool and a commercial manual contouring package to delineate the bladder on a serially imaged (10 cone beam CT volumes ) prostate patient. A previously presented shape analysis technique is used to quantitatively compare the observer variability.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Gareth Price and Chris Moore "Comparative evaluation of a novel 3D segmentation algorithm on in-treatment radiotherapy cone beam CT images", Proc. SPIE 6512, Medical Imaging 2007: Image Processing, 651238 (5 March 2007); https://doi.org/10.1117/12.709396
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Cited by 9 scholarly publications.
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KEYWORDS
Image segmentation

Radiotherapy

Bladder

Statistical modeling

Computed tomography

Principal component analysis

Optical spheres

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