We conduct an exhaustive survey of image thresholding methods, categorize them, express their formulas under a uniform notation, and finally carry their performance comparison. The thresholding methods are categorized according to the information they are exploiting, such as histogram shape, measurement space clustering, entropy, object attributes, spatial correlation, and local gray-level surface. 40 selected thresholding methods from various categories are compared in the context of nondestructive testing applications as well as for document images. The comparison is based on the combined performance measures. We identify the thresholding algorithms that perform uniformly better over nonde- structive testing and document image applications. © 2004 SPIE and IS&T. (DOI: 10.1117/1.1631316)

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Survey over image thresholding techniques and quantitative performance evaluation

An image guided catheter navigation system for navigating a region of a patient includes an imaging device, a tracking device, a controller, and a display. The imaging device generates images of the region of the patient. The tracking device tracks the location of the catheter in the region of the patient. The controller superimposes an icon representing the catheter onto the images generated from the imaging device based upon the location of the catheter. The display displays the image of the region with the catheter superimposed onto the image at the current location of the catheter.

Navigation system for cardiac therapies

A survey on image segmentation

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

Error measures for scene segmentation

The three-dimensional information from computerized tomographic scans has been transformed by image processing for use in stereotactic surgery. A lateral image of the target and calvarium can be superimposed on the lateral x-ray film taken at operation. Computer processing also eliminates extraneous data on the scan and gives the precise distance of the target from the midline. Testing the technique on a phantom shows it to be accurate to better than 0.5 cm. Application of the method for the stereotactic biopsy of a deep tumor is illustrated.

William A. Yasnoff

Papers

Error measures for scene segmentation

Stereotactic surgery with image processing of computerized tomographic scans.

Automated scene analysis of CT scans.