A survey on evaluation methods for image segmentation

http://www.bioimageanalysis.org/wp/wp-content/uploads/formidable/Survey_unsupervisedEvaluation.pdf

Image segmentation evaluation: A survey of unsupervised methods

Image segmentation is the partition of an image into a set of nonoverlapping regions whose union is the entire image. The image is decomposed into meaningful parts which are uniform with respect to certain characteristics, such as gray level or texture. In this paper, we propose a methodology for evaluating medical image segmentation algorithms wherein the only information available is boundaries outlined by multiple expert observers. In this case, the results of the segmentation algorithm can be evaluated against the multiple observers' outlines. We have derived statistics to enable us to find whether the computer-generated boundaries agree with the observers' hand-outlined boundaries as much as the different observers agree with each other. We illustrate the use of this methodology by evaluating image segmentation algorithms on two different applications in ultrasound imaging. In the first application, we attempt to find the epicardial and endocardial boundaries from cardiac ultrasound images, and in the second application, our goal is to find the fetal skull and abdomen boundaries from prenatal ultrasound images.

/pdf/a-methodology-for-evaluation-of-boundary-detection-26pzchmqmh.pdf

A methodology for evaluation of boundary detection algorithms on medical images

Interaction in the Segmentation of Medical Images: A Survey

https://academiccommons.columbia.edu/doi/10.7916/D82B97MG/download

A framework for evaluating image segmentation algorithms

A validation methodology for image segmentation methods is explored that is based on quality constrained cost analysis. In this methodology a segmentation method is evaluated by the cost reduction it provides relative to the cost of a full-interactive (manual) segmentation. This cost is constrained by a quality threshold, so that less-than-perfect segmentations are allowed. In this way, segmentation methods which are entirely different in nature can be compared objectively. The validation methodology is presented in its most general form, along with an example of its application to the comparison of segmentation methods. >

A methodology for the validation of image segmentation methods

Validation of the interleaved pyramid for the segmentation of 3D vector images

An improvement in the design of the hyperstack, a three-dimensional image segmentation tool, is described. It is based on a multiresolution approach which is mathematically supported by the diffusion equation. The blurring strategy, used to build the scale space, is outlined, including some difficulties that occur in view of the transition from 2-D to 3-D. The existing prototype, a hyperstack grounded on isointensity following, is extended by two novel ideas: weighted linking and stand-alone parents. The result of a segmented 3D SPECT image (of a liver) is shown. Theoretical considerations concerning the addition of feature information to guide the segmentation process are briefly mentioned. A flexible way to obtain several output images from one single hyperstack is outlined and the reduction of the sampling rate by means of interpolation, which will decrease the total amount of processing time, is investigated. >

Multiresolution segmentation of 3D images by the hyperstack

Crucial in the planning of a medical image archiving and communication system is the knowledge of the logistics of diagnostic images in and between departments. On the prerequisite that all requested images should be available at the referring department, knowing the average area (in cm2) of used film per kind of examination, as well as the necessary estimated spatial sampling frequency, an estimate is generated of the necessary intermediate storage buffers and the network capacity to the different departments.

Radiological Information Flow Between Departments And Out-Clinics In The Utrecht University Hospital In The Netherlands

The University Hospital Utrecht (UHU) has been the site for clinical evaluation of a prototype Picture Archiving and Communication System (PACS), as a part of the Dutch PACS project run by BAZIS, Phffips Medical Systems and the UHU in the period 19864989 k The 800 bed UHU moved in July 1989 to a new campus site facifity (Figure 1.). This offered the opportunity to design the new radiology department to be prepared for a future large scale PACS. The set-up includes an ergonomically designed digital reading room, a centrally located computer room, cooling and cabling, a video network covering the total department and facilities for teleradiology. Radiology, Radiotherapy and Nuclear Medicine are organized in one department.© (1990) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Integration of clinical routine digital imaging and advanced image processing through PACS

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