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Breast density (BD) has been advocated as a risk factor for the development of breast cancer. BD is typically measured from mammograms. However for longitudinal studies of patients at risk, BD can be better assessed using MRI due to the lack of ionizing radiation and the 3D capabilities of the technique. A fat-water (FW) imaging technique called RAD-GRASE was developed to acquire images of the entire breast in a few minutes and can generate fat-fraction maps, which can be used to assess BD. The time consuming manual segmentation on ~19 slices per exam can be challenging. In this paper, we present a method to automatically segment the breast tissue in FW images and yield FW profiles of the region of interest (ROIs).

Diffusion tensor imaging (DTI) is a Magnetic Resonance Imaging (MRI) technique that can reveal in vivo tissue microstructure by measuring diffusion of water in tissue. DTI has become an important tool in many clinical applications, such as assessment of white matter maturation, locating white matter lesions, and providing anatomical connectivity information. However, DTI usually requires long examination times due to the repetitive nature of the acquisition and is very sensitive to motion. These drawbacks have become the largest obstacles to full utilization of DTI. In this work, we propose to overcome these obstacles by using a model-based compressive imaging approach. Our approach consist of models to efficiently represent diffusion-encoded images and the corresponding recovery schemes based on compressive sensing (CS) principles. Our results indicate that the proposed model-based approach can allow reliable recovery of DTI signal from undersampled measurements and outperforms conventional CS recovery.

This paper describes the wavelet compression of ECG signals by JPEG2000. JPEG2000 is the latest international standard for compression of still images. JPEG2000 codec is designed to compress images and it can also be used to compress other signals. The desirable characteristics of the JPEG2000 codec, such as precise rate control and progressive quality, are retained in the presented ECG compression scheme. To compress the ECG data using a JPEG2000 code, the one-dimensional ECG sequence is processed to produce a two-dimensional matrix. This matrix is then encoded using JPEG2000.

The advantages of multi-shot radial fast spin-echo (RAD-FSE) MRI methods over conventional Fourier transformed (FT) MRI methods for obtaining high-resolution images with minimal motion- and flow-induced artifact are presented. The utility of post-processing methods used to obtain images with different T2-weighted contrast as well as T2 maps from a single radial set is also described. Applications are shown for three areas of clinical relevance, where motion precludes the use of conventional FT MRI methods to obtain high-resolution images. Results are shown for Diffusion-Weighted Imaging (DWI), and are compared to standard single-shot echo planar imaging (SSEPI). Results from cardiac imaging are presented and compared to conventional 2DFT-FSE methods. Results from RAD-FSE in abdominal imaging are also compared to single-shot fast spin-echo (SSFSE) and conventional 2DFT-FSE methods. The advantages of generating multiple T2-weighted images as well as T2 maps from a single radial set are demonstrated for body imaging.