A paper, "An Effective MR-Guided CT Network Training for Segmenting Prostate in CT Images", has been accepted for publication in IEEE Journal of Biomedical and Health Informatics
Donggyu's paper, "Spinal Stenosis Grading in Magnetic Resonance Imaging using Deep Convolutional Neural Networks", has been accepted at Spine
Soopil's paper, "Magnetic Resonance Imaging-based 3-Dimensional Fractal Dimension and Lacunarity Analyses may Predict the Meningioma Grade", has been accepted for publication in European Radiology
Ihsan's paper, "Real-time Tracking of Guidewire Robot Tips using Deep Convolutional Neural Networks on Successive Localized Frames ", has been accepted at IEEE Access.
Kwangdeok Seo joined MISPL.
Vinoth Kumar S joined MISPL internship. Welcome!
DGIST의 송혜주, 박희정 학생과 계명대학교의 정동규 학생이 4주간 하계 인턴을 진행하였습니다.
인턴기간 중 아래와 같은 일들을 수행하였습니다.
머신러닝과 딥러닝 이론공부
Pytorch를 이용한 딥러닝 프로그래밍
Classification, Segmentation, Enhancement, Registration 기법 이론 공부
안구 OCT 데이터 Segmentation
Congratulations!
Miguel and Mungi's paper, "Precise Separation of Adjacent Nuclei using a Siamese Neural Network", was accepted.
The challenge Team lead by Hugo Kuijf has finally released online the paper with all the results and analysis on the Automatic Segmentation of White Matter Hyperintensities.
Our submission ranked 6th among 20 participants of the challenge.
Please find the paper in the links below as well as our submissions and results
lIEEE TMI (early access): https://ieeexplore.ieee.org/document/8669968
lArxiv: https://arxiv.org/abs/1904.00682
lResearch Gate: https://www.researchgate.net/publication/331882631
lOur challenge submission: https://wmh.isi.uu.nl/results/misp
lOur post challenge submission: https://wmh.isi.uu.nl/results/misp-2
Sion An, Soopil Kim and Jaehoon Jeong joined MISPL.
We just made our code available in GitHub as well as our article has been made published on the Brainlesion:
Glioma, Multiple Sclerosis, Stroke and Traumatic Brain injuries, 2019 Book.
Find our code: https://github.com/miguel-dgist/mrbrains18
Find our article: 3D Patchwise U-Net with Transition Layers for MR Brain Segmentation
3 papers were accepted to 31th Workshop on Image Processing and Image Understanding (IPIU).
Philip’s paper, “Recurrent Attention Models for Tissue Histopathology Image Classification”, 제 31회 영상처리 및 이해에 관한 워크샵 (IPIU), 2019.
Mungi’s paper, “딥러닝 기반 워터쉐드 알고리즘을 이용한 세포 분할 기법”, 제 31회 영상처리 및 이해에 관한 워크샵(IPIU), 2019.
Gyeongmin’s paper, “클래스활성지도를 이용한 안구 질환에 따른 광간섭단층영상 내 특징 추출”, 제 31회 영상처리 및 이해에 관한 워크샵 (IPIU), 2019.
DGIST의 김은지, 안시온 학생과 이화여자대학교의 신예림 학생이 4주간 동계 인턴을 진행하였습니다.
인턴기간 중 아래와 같은 일들을 수행하였습니다.
머신러닝과 딥러닝 이론공부
TensorFlow를 이용한 딥러닝 프로그래밍
ResNet, Inception network, VGGNet 등 최신 Deep learning 기법들 구현
Deep learning을 이용한 의료영상 처리 및 성능평가
구현한 기법을 이용한 안구 OCT 데이터 Classification
Congratulations!
Eujins’s paper, “Enhancement of Perivascular Spaces using Densely Connected Deep Convolutional Neural Network”, accepted at IEEE Access, 2019.