Yonsei University · Medicine
Professor Ho Lee's research lab specializes in medical imaging, computational modeling, and energy systems, with a focus on advancing diagnostic technologies and energy recovery. The lab develops innovative deep learning and signal processing techniques for medical image analysis—particularly in chest X-ray and cone-beam CT—enabling low-dose, high-accuracy imaging for disease detection. It also explores laser-tissue interactions for ophthalmic therapies and designs efficient thermodynamic cycles for recovering low-grade heat and cold energy. The integration of AI, imaging science, and sustainable energy systems defines the lab’s interdisciplinary approach.
Figures are computed from collected data and may differ slightly.
The global pandemic of coronavirus disease 2019 (COVID-19) has resulted in an increased demand for testing, diagnosis, and treatment. Reverse transcription polymerase chain reaction (RT-PCR) is the definitive test for the diagnosis of COVID-19; however, chest X-ray radiography (CXR) is a fast, effective, and affordable test that identifies the possible COVID-19-related pneumonia. This study investigates the feasibility of using a deep learning-based decision-tree classifier for detecting COVID-1
Vehicle classification data are used for numerous transportation applications. Most of the classification data come from permanent in-pavement sensors or temporary sensors mounted on the pavement. This study developed a lidar-based classification system that used data from sensors mounted in a side-fire configuration next to the road. The classification system first distinguished between vehicle returns and nonvehicle returns, and then clustered the vehicle returns into individual vehicles. An a
Volumetric cone-beam CT (CBCT) images are acquired repeatedly during a course of radiation therapy and a natural question to ask is whether CBCT images obtained earlier in the process can be utilized as prior knowledge to reduce patient imaging dose in subsequent scans. The purpose of this work is to develop an adaptive prior image constrained compressed sensing (APICCS) method to solve this problem. Reconstructed images using full projections are taken on the first day of radiation therapy trea
Selective laser targeting of the retinal pigment epithelium (RPE) is an attractive method for treating RPE-associated disorders. We are developing a method for optically detecting intracellular microcavitation that can potentially serve as an immediate feedback of the treatment outcome. Thermal denaturation or intracellular cavitation can kill RPE cells during selective targeting. We examined the cell damage mechanism for laser pulse durations from 1 to 40 micros ex vivo. Intracellular cavitatio
An asymmetric half beam blocker-based FDK acquisition and reconstruction technique has been established. The proposed scheme enables simultaneous detection of patient specific scatter and complete volumetric CBCT reconstruction without additional requirements such as prior images, dual scans, or moving strips.
In this work, energy and exergy analyses are carried out for a combined cycle consisting of an organic Rankine cycle (ORC) and a liquefied natural gas (LNG) Rankine cycle for the recovery of low-grade heat sources and LNG cold energy. The effects of the turbine inlet pressure and the working fluid on the system performance are theoretically investigated. A modified temperature-enthalpy diagram is proposed, which can be useful to see the characteristics of the combined cycle, as well as the tempe
During pulsed laser lithotripsy, the calculus is subject to a strong recoil momentum which moves the calculus away from laser delivery and prolongs the operation. This study was designed to quantify the recoil momentum during Ho:YAG laser lithotripsy. The correlation among crater shape, debris trajectory, laser-induced bubble and recoil momentum was investigated. Calculus phantoms made from plaster of Paris were ablated with free running Ho:YAG lasers. The dynamics of recoil action of a calculus
Loop detectors are the most common sensors used to collect freeway management data. There has been considerable research to screen the quality of loop detector data, but some significant detector errors have not received much attention because of the difficulty of identifying their occurrence. This study examines one such error, pulse breakup, in which what should be a single pulse from a vehicle breaks up into two or more pulses because the detector momentarily drops out. An algorithm is develo
A ray-driven backprojector is based on ray-tracing, which computes the length of the intersection between the ray paths and each voxel to be reconstructed. To reduce the computational burden caused by these exhaustive intersection tests, we propose a fully graphics processing unit (GPU)-based ray-driven backprojector in conjunction with a ray-culling scheme that enables straightforward parallelization without compromising the high computing performance of a GPU. The purpose of the ray-culling sc
This paper proposes a binary moving-blocker (BMB)-based technique for scatter correction in cone-beam computed tomography (CBCT). In concept, a beam blocker consisting of lead strips, mounted in front of the x-ray tube, moves rapidly in and out of the beam during a single gantry rotation. The projections are acquired in alternating phases of blocked and unblocked cone beams, where the blocked phase results in a stripe pattern in the width direction. To derive the scatter map from the blocked pro
Open papers in the app to read, cite, and organize with AI.