Tracking dataset multi-instrument Endo-Visceral Surgery and multi-instrument in vivo | Single-instrument Retinal Microsurgery Instrument Tracking dataset, Multi-instrument Endo-Visceral surgery and multi-instrument in vivo images | 940 frames of the training data (4479 frames) and 910 frames for the test data (4495 frames) | Detect the two-dimensional position of different medical instruments in endoscopy and microscopy surge | Convolutional Detection regression network | Accuracy of 0.94 | Robotic Surgery | [2] : [119] |
CT/PET- CT/SPECT | Nuclear MRIs 3D | 124 double echo steady state from 17 patients | Diagnose possible soft tissue injuries | DeepResolve, a 3D-CNN model | MSE of 0.008 | Traumatology | [2] [160] |
Retinal 3D images obtained by Optical Coherence Tomography | 269 patients with AMD, 115 control patients | Retina age-related macular degeneration diagnostic | CNN | AUC of 0 | Ophthalmology | [77] | |
123I-fluoropropyl carbomethoxy-iodophenyl nortropane single-photon emission computed tomography (FP-CIT SPECT) 2D images | 431 patient cases | Automatic interpretation system in Parkinson’s disease | CNN | Accuracy of 0.96 | Neurology- Psychiatry | [79] | |
Abdominal CT 3D images | 231 computed abdominal | CAD system to classify tomographyes and evaluate the malignity degree in gastro-intestinal stromal tumors (GISTs) | Hybrid system between convolutional networks and radiomics | AUC of 0.882 | Oncology | [161] | |
CT image patches 2D | 14,696 images from 120 patients with proven diagnose | CAD system to diagnose interstitial lung disease | CNN | Accuracy of 0.85 | Pneumology | [85] | |
3D MRI and PET | 93 Alzheimer Disease, 204 MCI Mild Cognitive Impairment converters and normal control subjects | CAD for early Alzheimer disease stages | Multimodal DBM | Accuracy of 0.95, 0.85 and 0.75 for the three use cases | Neurology- Psychiatry | [2] ; [92] | |
CT/PET- CT/SPECT | CT images, MRI images and PET images | 6776 images for training and 4166 for tests | Classify medical diagnostic images according to the modality they were produced and classify illustrations according to their production attributes | CNN and a synergic signal system | Accuracy of 0.86 | Various | [2] [108] |