Pinned Repositories
AI_FCH
AI_FCH_NEW
Unsupervised PET/CT analysis with INN
BraTS2018-tumor-segmentation
We provide DeepMedic and 3D UNet in pytorch for brain tumore segmentation. We also integrate location information with DeepMedic and 3D UNet by adding additional brain parcellation with original MR images.
cic_gui_clean
CSN_chexpert
Experiments with adaptive instance normalization on chexpert
DL_BRATS
brain-tumor segmentation with U-net. *
ElastixModelZoo
Model Zoo for parameter settings in Elastix, ITKElastix and SimpleElastix
magic_ultrasound
detecting deformations
Useful_radom_things_TF
Random personally useful things to avoid writing same code multiple times
video_segmentation_annotator
basic video segmentation annotator in kivy
ljarabek's Repositories
ljarabek/CSN_chexpert
Experiments with adaptive instance normalization on chexpert
ljarabek/DL_BRATS
brain-tumor segmentation with U-net. *
ljarabek/AI_FCH
ljarabek/AI_FCH_NEW
Unsupervised PET/CT analysis with INN
ljarabek/BraTS2018-tumor-segmentation
We provide DeepMedic and 3D UNet in pytorch for brain tumore segmentation. We also integrate location information with DeepMedic and 3D UNet by adding additional brain parcellation with original MR images.
ljarabek/cic_gui_clean
ljarabek/ElastixModelZoo
Model Zoo for parameter settings in Elastix, ITKElastix and SimpleElastix
ljarabek/magic_ultrasound
detecting deformations
ljarabek/medslike
Inferring tumor location from body surface data. https://drive.google.com/open?id=1njJyq18J6RnwVu2MXkT_tVk_jp5IWw5C
ljarabek/Useful_radom_things_TF
Random personally useful things to avoid writing same code multiple times
ljarabek/video_segmentation_annotator
basic video segmentation annotator in kivy
ljarabek/MedLabelMe_moj
Segmentation annotation tool for 3D medical images
ljarabek/MUNIT-Tensorflow
MUNIT visualizer test**
ljarabek/normal_mr
experiments
ljarabek/pyTsetlinMachine
Implementation of the Tsetlin Machine, Convolutional Tsetlin Machine and Regression Tsetlin Machine
ljarabek/ULTRASOUND_MASTER
Experiments on supervised and unsupervised learning for detecting fasciculations in ultrasound video