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Data augmentation using Generative Adversarial Network in Chest X-ray

영상의학과 이상민A 교수님 협력연구

Data augmentation techniques for high-resolution chest X-ray images using GANs and latent space disentanglement 

Disentanglement of Latent Space of GANs

영상의학과 이상민A 교수님 협력연구

Data augmentation techniques for high-resolution chest X-ray images using GANs and latent space disentanglement 

Spine segmentation using Deep Learning

세브란스/강남세브란스/분당서울대병원 협력연구

Fully automated 3D segmentation and separation of multiple cervical vertebrae in CT images using a 2D convolutional neural network

Action recognition in operating rooms

마취과 김성훈 교수님 협력연구

Automated hand hygiene monitoring system in operating rooms using a combination of pose estimation and action recognition

Unsupervised Anomaly Detection using GANs

영상의학과 이상민A, 홍길선 교수님 협력연구

Unsupervised anomaly detection in chest X-ray and wholebody CT images using GANs

Bio-medical signal processing

심장내과 송종민 교수님 협력연구

Fully automated heart disease classification using convolutional neural networks

Segmentation

Airway segmentation (영상의학과 서준범 교수님 협력연구)

Improvement of fully automated airway segmentation on volumetric computed tomographic images using a 2.5D dimensional convolutional  neural net, MIA 2019.

Segmentation

Pancreas segmentation (영상의학과 김형중 교수님 협력연구)

Robustness and accuracy enhancement of pancreas segmentation using domain adaptation with 3D u-net between multi-center abdominal CT scans, KCR 2018.

Segmentation

Kidney segmentation (비뇨의학과 김청수, 건강의학과 경윤수 교수님 협력연구)

Robustness and accuracy enhancement of pancreas segmentation using domain adaptation with 3D u-net between multi-center abdominal CT scans, KCR 2018.

Classification

Pathological diagnosis in colonoscopy (소화기내과 변정식 교수님 협력연구)

Endoscopic diagnosis and treatment plan for colorectal polyps using a deep learning model, submitted.

Classification

Pathological diagnosis in colonoscopy (소화기내과 변정식 교수님 협력연구)

Endoscopic diagnosis and treatment plan for colorectal polyps using a deep learning model, submitted.

Classification

Chest X-ray classification (영상의학과 서준범, 이상민B 교수님 협력연구)

Curriculum learning from patch to image for pulmonary abnormal pattern screening in chest-PA x-ray: validation on multi-center datasets, RSNA 2018.

Detection

Quantification of renal transplant rejection (병리과 고현정 교수님 협력연구)

A fully automated system using a convolutional neural network to predict renal allograft rejection: extra-validation with giga-pixel immunostained slides, Scientific Reports 2019.

Detection

Breast cancer (병리과 공경엽 교수님 협력연구)

A fully automated system to predict not only whether digital slide has metastasis or not, but also localize the active tumor regions using an ensemble of CNN-based classification models in real time.

Survival Analysis

Chronic obstructive pulmonary disease (영상의학과 서준범 교수님 협력연구)

Evaluation of deep radiomics from chest computed tomography (CT) as possible predictors on the mortality of patients with chronic obstructive pulmonary disease.

Survival Analysis

Liver cancer (소화기내과 김강모 교수님 협력연구)

Development of machine learning-based clinical decision support system for hepatocellular carcinoma, submitted.

Survival Analysis

Lung cancer (영상의학과 이상민B 교수님 협력연구)

Deep radiomics approach for prediction of mortality in lung cancer.

Super-resolution

CT kernel conversion (영상의학과 서준범, 이상민B 교수님 협력연구)

CT kernel conversions using convolutional neural net for super-resolution with simplified SE blocks and progressive learning among smooth and sharp kernels, SPIE 2019.

Super-resolution

MRI denoising (영상의학과 정승채 교수님 협력연구)

MRI Compressed Sensing Image Reconstruction using deep learning.

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