CUDA Spotlight: Tools for Microsurgeons
Compute The Cure
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This week's Spotlight is on Kang Zhang, a PhD candidate in Electrical and Computer Engineering at Johns Hopkins University. His interests include GPU-accelerated biomedical imaging.
NVIDIA: Kang, what are you working on at Johns Hopkins?
Kang: My current research focuses on interventional Optical Coherence Tomography (OCT) technology for microsurgery.
Conventionally, visualization during microsurgery is realized with a surgical microscope, which limits the surgeon’s field of view and causes limited depth perception of micro-structures and tissue planes beneath the surface.
Such issues commonly exist in many kinds of microsurgeries such as ophthalmic surgery, neurological surgery and otolaryngologic surgery.
OCT is a new imaging modality capable of non-invasive 3D micrometer-resolution imaging, which makes it highly suitable for guiding microsurgery. As part of my PhD work, I developed an ultra-high-speed, real-time OCT imaging system using a hardware-software platform based on GPU technology.
NVIDIA: How does GPU computing play a role in your work?
Therefore, current high-speed OCT systems are usually non-realtime and working in a “post-processing mode,” which limits its interventional application. To solve these bottlenecks, I use CUDA technology to accelerate both the OCT image reconstruction and visualization, in particular, 3D volume rendering.
NVIDIA: How did you become interested in this area?
The CUDA acceleration is highly cost-effective compared to the overall cost of an OCT system and no optical modification is required. I am also working on developing a CUDA-based high data throughput imaging platform for general purpose applications.
NVIDIA: What are some advantages of working with CUDA?
NVIDIA: What are the potential real-world applications?
NVIDIA: As computing becomes faster, what can we look forward to?
Kang Zhang’s Biography: