High frame-rate cardiac ultrasound imaging with deep learning

Cardiac ultrasound imaging requires a high frame rate in order to capture rapid motion. This can be achieved by multi-line acquisition (MLA), where several narrow-focused received lines are obtained from each wide-focused transmitted line. This shortens the acquisition time at the expense of introducing block artifacts. In this paper, we propose a data-driven learning-based approach to improve the MLA image quality. We train an end-to-end convolutional neural network on pairs of real ultrasound cardiac data, acquired through MLA and the corresponding single-line acquisition (SLA). The network achieves a significant improvement in image quality for both $5-$ and $7-$line MLA resulting in a decorrelation measure similar to that of SLA while having the frame rate of MLA.Comment: To appear in the Proceedings of MICCAI, 201

Acoustical structured illumination for super-resolution ultrasound imaging.

Structured illumination microscopy is an optical method to increase the spatial resolution of wide-field fluorescence imaging beyond the diffraction limit by applying a spatially structured illumination light. Here, we extend this concept to facilitate super-resolution ultrasound imaging by manipulating the transmitted sound field to encode the high spatial frequencies into the observed image through aliasing. Post processing is applied to precisely shift the spectral components to their proper positions in k-space and effectively double the spatial resolution of the reconstructed image compared to one-way focusing. The method has broad application, including the detection of small lesions for early cancer diagnosis, improving the detection of the borders of organs and tumors, and enhancing visualization of vascular features. The method can be implemented with conventional ultrasound systems, without the need for additional components. The resulting image enhancement is demonstrated with both test objects and ex vivo rat metacarpals and phalanges

Microwave imaging techniques for biomedical applications

Microwaves have been considered for medical applications involving the detection of organ movements and changes in tissue water content. More particularly cardiopulmonary interrogation via microwaves has resulted in various sensors monitoring ventricular volume change or movement, arterial wall motion, respiratory movements, pulmonary oedema, etc. In all these applications, microwave sensors perform local measurements and need to be displaced for obtaining an image reproducing the spatial variations of a given quantity. Recently, advances in the area of inverse scattering theory and microwave technology have made possible the development of microwave imaging and tomographic instruments. This paper provides a review of such equipment developed at Suplec and UPC Barcelona, within the frame of successive French-Spanish PICASSO cooperation programs. It reports the most significant results and gives some perspectives for future developments. Firstly, a brief historical survey is given. Then, both technological and numerical aspects are considered. The results of preliminary pre-clinical assessments and in-lab experiments allow to illustrate the capabilities of the existing equipment, as well as its difficulty in dealing with clinical situations. Finally, some remarks on the expected development of microwave imaging techniques for biomedical applications are given.Peer ReviewedPostprint (published version

Advances on CMOS image sensors

This paper offers an introduction to the technological advances of image sensors designed using complementary metal–oxide–semiconductor (CMOS) processes along the last decades. We review some of those technological advances and examine potential disruptive growth directions for CMOS image sensors and proposed ways to achieve them. Those advances include breakthroughs on image quality such as resolution, capture speed, light sensitivity and color detection and advances on the computational imaging. The current trend is to push the innovation efforts even further as the market requires higher resolution, higher speed, lower power consumption and, mainly, lower cost sensors. Although CMOS image sensors are currently used in several different applications from consumer to defense to medical diagnosis, product differentiation is becoming both a requirement and a difficult goal for any image sensor manufacturer. The unique properties of CMOS process allows the integration of several signal processing techniques and are driving the impressive advancement of the computational imaging. With this paper, we offer a very comprehensive review of methods, techniques, designs and fabrication of CMOS image sensors that have impacted or might will impact the images sensor applications and markets