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]