Already, physicians are using sophisticated pattern-recognition systems to read ECGs, EEGs, Pap smears, mammograms, chest radiographs, angiograms and MR, CT and PET images. Recently, several image-based systems for diagnosing cancer, cardiovascular disease and other conditions crossed regulatory and commercial thresholds. In May, for example, the FDA approved AutoPap, the first automated system for primary screening of Pap smears. In June, the FDA approved ImageChecker, an image-based decision support system that helps radiologists identify women at risk for breast cancer. There are several investigational pattern-recognition systems for mammograms, but this is the first one to be approved, says David G. Brown, PhD, the FDA's chief scientist, electronics and computer science division.
Radiologists miss a significant number of lesions due to lack of attention.
This will help. Improving objectivity in reading images The potential benefits of computers reading images is obvious and compelling. Provided they are well programmed and fed high-quality data, computers can analyze images consistently, reliably and with a high degree of accuracy. They don't get tired or have bad days, and they maintain a constant level of expertise. Computerized pattern recognition will raise the bar by bringing everyone up to the expert level of performance.