Major Bio-Medical Imaging Modalities
Our projects involve robust Machine Learning (ML)/Deep Learning (DL)/Artificial Intelligence (AI) techniques and we apply them to various bio-medical imaging modalities in an organ/disease-agnostic manner. We do not discriminate against any type of data/organs/diseases as we strongly believe in "Building Healthcare - Data as Capital" motto! :-)
Epifluorescence - Denoising, Segmentation, Clustering
Immunofluorescence - RF-HEp-2, HEp-2SegZoo
Fundoscopy - Retinal-seg
Confocal - Denoising, Deconvolution, Segmentation
IHC
FISH
Cryo-EM - Denoising
MALDI-MS
ErythroNet
Brain MRI - MAC-Multiphase segmentation, MSP-Mid saggital plane, Skull stripping, Symmetry, SIMMER, Bleeds, Denoising, iSPi
Liver MRI
MREntNet
MRA
fMRI - LeaS
Mammography - Segmentation, Enhancement, Registration
DBT
Thermal imaging
Denoising
Chest X-ray (CXR) - PICCLineNet, TracNet, Analysis, LungSeg, LungBoundary, TBScreen
Cardiomegaly
Organ Segmentation
CBXIR
DEXA