Targeting the centromeres of chromosomes 3, 7, 17 (CEP3, 7, 17) and the 9p21-locus (LSI9p21) for diagnosing bladder cancer (BC) is time- and cost-intensive and requires a manual investigation of the sample by a well-trained investigator thus overall limiting its use in clinical diagnostics and large-scaled epidemiological studies. Here we introduce a new computer-assisted FISH spot analysis tool enabling an automated, objective and quantitative assessment of FISH patterns in the urinary sediment. Utilizing a controllable microscope workstation, the microscope software Scan boolean AND R was programmed to allow automatic batch-scanning of up to 32 samples and identifying quadruple FISH signals in DAPI-scanned nuclei of urinary sediments. The assay allowed a time- and cost-efficient, automated and objective assessment of CEP3, 7 and 17 FISH signals and facilitated the quantification of nuclei harboring specific FISH patterns in all cells of the urinary sediment. To explore the diagnostic capability of the developed tool, we analyzed the abundance of 51 different FISH patterns in a pilot set of urine specimens from 14 patients with BC and 21 population controls (PC). Herein, the results of the fully automated approach yielded a high degree of conformity when compared to those obtained by an expert-guided re-evaluation of archived scans. The best cancer-identifying pattern was characterized by a concurrent gain of CEP3, 7 and 17. Overall, our automated analysis refines current FISH protocols and encourages its use to establish reliable diagnostic cutoffs in future large-scale studies with well-characterized specimens-collectives. (C) 2014 Elsevier Inc. All rights reserved.