Visual x-ray image processing (XRIP) represents a fundamental component of catheter-based cardiovascular interventions (CBCVIs). To date, no data are available to define XRIP in this setting. To characterize CBCVI XRIP, we developed a computer-based method allowing continuous temporal–spatial analysis of data recorded by a head-mounted eye-tracking device. Quantitative analysis of gaze duration of an expert operator (EO) revealed that the average time in minutes spent viewing the images on the display screen was 39.5%±13.6% and 41.5%±18.3% of the total recorded time in coronary angiography (CA) and in CA followed by CBCVI, respectively. Qualitative analysis of gaze data of the EO revealed consistent focus on the center point of the screen. Only if suspicious findings were detected did gaze move toward the target. In contrast, a novice operator (NO) observing a subset of cases viewed coronary artery segments separately and sequentially. The developed methodology allows continuous registration and analysis of gaze data for analysis of XRIP strategies of EOs in live-cases scenarios and may assist in the transfer of experts’ reading skills to novices.
Page segmentation into text and non-text elements is an essential preprocessing step before optical character
recognition (OCR) operation. In case of poor segmentation, an OCR classification engine produces garbage
characters due to the presence of non-text elements. This paper describes modifications to the text/non-text
segmentation algorithm presented by Bloomberg,1 which is also available in his open-source Leptonica library.2The modifications result in significant improvements and achieved better segmentation accuracy than the original
algorithm for UW-III, UNLV, ICDAR 2009 page segmentation competition test images and circuit diagram