Ga-Yeong Lee
Korea Advanced Institute of Science and Technology · Medicine
About the Lab
Professor Ga-Yeong Lee's research lab specializes in the intersection of deep learning and medical image analysis, with a focus on enhancing saliency detection through the integration of hand-crafted low-level and deep neural network-derived high-level features. The lab also investigates traditional herbal medicines as potential adjuvants in oncology and hepatology, particularly for overcoming multidrug resistance in colorectal cancer and treating refractory edema in cirrhotic patients. Additionally, the lab explores data-efficient deep learning techniques for artistic image translation, such as sketch-to-line conversion, using unpaired data. These diverse research directions reflect a strong commitment to improving clinical diagnostics and therapeutic outcomes through intelligent image processing and integrative medicine.
Research Overview
Research Output Trend
Figures are computed from collected data and may differ slightly.
Selected Papers
15Recent advances in saliency detection have utilized deep learning to obtain high level features to detect salient regions in a scene. These advances have demonstrated superior results over previous works that utilize hand-crafted low level features for saliency detection. In this paper, we demonstrate that hand-crafted features can provide complementary information to enhance performance of saliency detection that utilizes only high level features. Our method utilizes both high level and low lev
Objectives . Multidrug resistance (MDR) is the major reason for the failure of chemotherapy in colorectal cancer (CRC), and the primary determinant of MDR in CRC patients is active drug efflux owing to overexpression of P‐glycoprotein (P‐gp) in cancer tissues. Despite research efforts to overcome P‐gp‐mediated drug efflux, the high toxicity of P‐gp inhibitors has been a major obstacle for the clinical use of these agents. The aim of this study was to review the literature for potential P‐gp reve
Recent advances in saliency detection have utilized deep learning to obtain high-level features to detect salient regions in scenes. These advances have yielded results superior to those reported in past work, which involved the use of hand-crafted low-level features for saliency detection. In this paper, we propose ELD-Net, a unified deep learning framework for accurate and efficient saliency detection. We show that hand-crafted features can provide complementary information to enhance saliency
RATIONALE: Refractory edema is characterized by persistent swelling which does not react to diuretic use and sodium restriction. Traditional herbal medicine, Gwack Rhyung Tang and Chunggan extract effectively treated refractory lower limb edema caused by cirrhosis and improved liver function. PATIENT CONCERNS: A 64-year-old male patient with a history of hypertension, diabetes mellitus, hepatic encephalopathy, and cellulitis presented lower limb edema which did not react to diuretics for more th
Converting hand-drawn sketches into clean line drawings is a crucial step for diverse artistic works such as comics and product designs. Recent data-driven methods using deep learning have shown their great abilities to automatically simplify sketches on raster images. Since it is difficult to collect or generate paired sketch and line images, lack of training data is a main obstacle to use these models. In this paper, we propose a training scheme that requires only unpaired sketch and line imag
Recent advances in saliency detection have utilized deep learning to obtain high level features to detect salient regions in a scene. These advances have demonstrated superior results over previous works that utilize hand-crafted low level features for saliency detection. In this paper, we demonstrate that hand-crafted features can provide complementary information to enhance performance of saliency detection that utilizes only high level features. Our method utilizes both high level and low lev
ABSTRACT Malaria drug interactions in cytostatic or inhibitory in vitro assays or suppression models in vivo can be different than curative killing interactions. In the pharmacodynamic high parasitemia Plasmodium berghei ANKA-luciferase mouse blood-stage model, we investigated curative interaction analysis of multiple, daily dosed, short half-life, artesunate or single-dose, long half-life, pyronaridine against three single-dose, long half-life, quinolines—chloroquine, amodiaquine, and tafenoqui
Objectives: This study aimed to emphasize the importance of accurate and timely diagnosis of acute abdominal pain with simple radiography by reporting a case of gastrointestinal perforation.Methods: We closely observed the diagnosis and progress of acute abdominal pain after biliary stent and reviewed the outline of gastrointestinal perforation.Results: Patient diagnosed with urethral cancer metastasis to lung and peritoneum was treated with complex Korean medicinal treatments to deal with anore
This project of research - creation is born from the desire to make intelligeble the logic of the birth of the movement such as the dancer feels it. The birth of the dance movement works with the birth of ideas. How do the physical materials give birth to ideas? How can the ideas produce physical materials? To answer these questions, the experiences of the choreographer dancer are analyzed during the process of a creation on the four elements. The work on the element « Earth » clarifies the rela
Research Areas
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