An ANN-based HRV classifier for cardiac health prognosis.

A multi-layer artificial neural network (ANN)-based heart rate variability (HRV) classifier has been proposed, which gives the cardiac health status as the output based on HRV of the patients independently of the cardiologists' view. The electrocardiogram (ECG) data of 46 patients were recorded in the out-patient department (OPD) of a hospital and HRV was evaluated using self-designed autoregressive-model-based technique. These patients suspected to be suffering from cardiac abnormalities were thoroughly examined by experienced cardiologists.

Neural network based focal liver lesion diagnosis using ultrasound images.

Present study proposes a computer-aided diagnostic system to assist radiologists in identifying focal liver lesions in B-mode ultrasound images. The proposed system can be used to discriminate focal liver diseases such as Cyst, Hemangioma, Hepatocellular carcinoma and Metastases, along with Normal liver. The study is performed with 111 real ultrasound images comprising of 65 typical and 46 atypical images, which were taken from 88 subjects.

Enhancement of the ultrasound images by modified anisotropic diffusion method.

Speckle is a primary factor which degrades the contrast resolution and masks the meaningful texture information present in an ultrasound image. Its presence severely hampers the interpretation and analysis of ultrasound images. When speckle reduction technique is applied for visual enhancement of ultrasound images, it is to be kept in mind that blurring associated with speckle reduction should be less and fine details are properly enhanced.