Title :
Generalized Caseview applied to prostate cancer prognosis
Author :
Levy, Pierre P. ; Bardier, Armelle ; Doublet, Jean-Dominique ; Sibony, Mathilde
Author_Institution :
Public Health Department Hÿpital Tenon, Assistance Publique Hÿpitaux de Paris, 4 rue de la Chine, 75970, Cedex 20, France
Abstract :
The interpretation of results of any study using large tables with series of numbers is always difficult. Generalized Case View Method (GCm) allows translating these tables of numbers into an image. The Method identifies each informational entity in the table with a “pixel”, forming what we call an “infoxel”. The sum of all informational entities becomes an image, the Generalized Caseview. The method consists of two steps: the first one is to define the reference frame while the second is to visualize data through the reference frame. The “infoxels” that constitute the reference frame should be organized according to three criteria: binary, nominal and ordinal. Here this method has been applied to visualize the results of a study about prostate cancer spread. This paper exemplifies the usefulness of associating a classical statistical tool with Generalized Caseview method to solve a biomedical problem.
Keywords :
Anatomy; Biomedical imaging; Biopsy; Data visualization; Histograms; Pathology; Prostate cancer; Public healthcare; Statistical analysis; Tumors; Artificial Intelligence; Biopsy; Computer Graphics; Decision Support Systems, Clinical; Diagnosis, Computer-Assisted; Humans; Male; Pattern Recognition, Automated; Prostatic Neoplasms; Reproducibility of Results; Sensitivity and Specificity; User-Computer Interface;
Conference_Titel :
Engineering in Medicine and Biology Society, 2008. EMBS 2008. 30th Annual International Conference of the IEEE
Conference_Location :
Vancouver, BC
Print_ISBN :
978-1-4244-1814-5
Electronic_ISBN :
1557-170X
DOI :
10.1109/IEMBS.2008.4650368