PhD Defense: "Separation, Denoising, and Reconstruction of 4D Embryonic Cardiac Microscopy Datasets for Improved Visualization and Flow Analysis"

Sandeep Bhat

February 20th (Wednesday), 9:30am
Harold Frank Hall (HFH), Rm 4164

Cardiac development is a highly dynamic process. Currently there is a need for image processing techniques for image component separation, denoising, and reconstruction of high frame-rate, high resolution, multi-dimensional cardiac datasets acquired during live (in-vivo) imaging of the embryonic heart. Such methods would help in quantifying blood flow and tissue deformation during cardiac development, thus facilitating a better understanding of cardiac morphogenesis.

The first part of this thesis deals with improving the specificity in label-free, high speed brightfield (BF) microscopy images. We propose a motion-based separation algorithm to decompose a single-channel 3D+time volume into three channels showing cyclic heart-wall, static support structures, and transient blood cells. The technique is based on non-uniform temporal synchronization, selection, and combination of images from multiple cardiac cycles and z-sections to produce 3D+time image volumes of one full cardiac cycle that are highly suitable for 3D visualization and analysis of the individual structures’ dynamics in the embryonic heart.

In the second part, we develop a computational noise reduction technique to enhance optical coherence tomography (OCT) datasets of cyclically moving structures. This allows imaging dynamic structures within scattering tissue like the embryonic mouse heart, while preserving temporal and spatial resolution.

In the final part, we discuss reconstruction of a 3D+time cardiac volume from multiple high-speed 2D+time sequences that are sequentially acquired along multiple heart beats. Our technique uses image based retrospective gating for temporal alignment but mitigates the cumulative registration errors by using a second set of 2D+time sequences acquired at an angle orthogonal to the first. By globally minimizing an objective criterion that depends on the similarity of the data present at the intersecting slices, the two sets are registered and fused to obtain a high-speed high-resolution multi-dimensional reconstruction of the heart.

The methods developed in this thesis improve the visualization of cardiac BF and OCT datasets over existing image processing techniques, and enable quantitative study of cardiac morphogenesis.

About Sandeep Bhat:

Sandeep Bhat obtained the B.E degree in Electronics and Communications from Vishweshwaraiah Technological University (VTU), India in 2003 where he secured the Second Rank for the University. He was a Senior Engineer in Ittiam Systems Pvt. Ltd., India until 2007, where he worked in the Media Processing Group on developing handheld and mobile multi-media devices. He secured his M.S degree in Electrical and Computer Engineering from University of California, Santa Barbara in 2008, and is currently pusuing his Ph.D in the same institute under the guidance of Prof. Michael Liebling. His research interests include image processing and computer vision, with particular focus on biomedical applications. Mr. Bhat won the outstanding teaching assitant award from the ECE, UCSB, in 2009. He was a one of the nine finalists chosen for "Grand Challenges in Bioengineering" competition at the UC systemwide Bioengineering Symposium in 2011. He received the Spring Dissertation Fellowship and the Summer Fellowship in 2012 from ECE, UCSB.

Hosted by: Professor Michael Liebling