Nowadays, with the increase in the dreadful diseases, huge amount of database is produced in hospitals and are exponentially increasing day by day. Utilizing these medical images after efficient classification plays a major role in case based reasoning and supports in clinical decision making. Therefore, it is important to classify these images and access them accurately. A modality classifier ...

We introduce a new approach to medical image analysis that combines deformable model methodologies with concepts from the field of artificial life. In particular, we propose "deformable organisms", autonomous agents whose task is the automatic segmentation, labeling, and quantitative analysis of anatomical structures in medical images. Analogous to natural organisms capable of voluntary movemen...

Ultrasound (US) is one of the most widely used imaging modalities in medical diagnosis. It has advantages real-time, low cost, noninvasive nature, and easy to operate. However, it also unique disadvantages strong artifacts noise high dependence on experience doctors. In order overcome shortcomings ultrasound diagnosis help doctor improve accuracy efficiency diagnosis, many computer aided (CAD) ...

An image quality matrix provides a significant principle for objectively observing an based on alteration between the original and distorted images. During past two decades, novel universal assessment has been developed with ability of adaptation human visual perception measuring difference degraded from reference image, namely structural similarity index. Structural since widely used in variou...

Deep learning (DL) models are currently not widely deployed for critical tasks such as in health. This is attributable to the "black box", making it difficult gain trust of practitioners. paper proposes use visualizations enhance performance verification, improve monitoring, ensure understandability, and interpretability needed practitioners' confidence. These demonstrated through development a...