29 citations · 42 across the 12 of their papers we have counts for
5 papers · 1 filter
Deep learning segmentation of fibrous cap in intravascular optical coherence tomography images
Juhwan Lee, Justin N. Kim, Luis A. P. Dallan +7
Thin-cap fibroatheroma (TCFA) is a prominent risk factor for plaque rupture. Intravascular optical coherence tomography (IVOCT) enables identification of fibrous cap (FC), measurem…
Automated segmentation of microvessels in intravascular OCT images using deep learning
Juhwan Lee, Justin N. Kim, Lia Gomez-Perez +10
To analyze this characteristic of vulnerability, we developed an automated deep learning method for detecting microvessels in intravascular optical coherence tomography (IVOCT) ima…
Prediction of stent under-expansion in calcified coronary arteries using machine-learning on intravascular optical coherence tomography
Yazan Gharaibeh, Juhwan Lee, Vladislav N. Zimin +12
BACKGROUND Careful evaluation of the risk of stent under-expansions before the intervention will aid treatment planning, including the application of a pre-stent plaque modificatio…
OCTOPUS -- optical coherence tomography plaque and stent analysis software
Juhwan Lee, Justin N. Kim, Yazan Gharaibeh +8
Compared with other imaging modalities, intravascular optical coherence tomography (IVOCT) has significant advantages for guiding percutaneous coronary interventions. To aid IVOCT…
Attention-Aware Linear Depthwise Convolution for Single Image Super-Resolution
Seongmin Hwang, Gwanghuyn Yu, Cheolkon Jung +1
Although deep convolutional neural networks (CNNs) have obtained outstanding performance in image superresolution (SR), their computational cost increases geometrically as CNN mode…