This paper presents a large publicly available multi-center lumbar spine magnetic resonance imaging (MRI) dataset with reference segmentations of vertebrae, intervertebral discs (IVDs), and spinal canal. The dataset includes 447 sagittal T1 and T2 MRI series from 218 patients with a history of low...
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2b) and CT images were manually segmented to extract 3D labels. The extraction of the region of interest allowed the objective anatomical features of the radius and ulna to be recognized with high accuracy. (2) DRR images were automatically generated from CT images aligned to actual X-ray ...
The automatic image segmentation of the spine obtained from a computed tomography (CT) image is important for diagnosing spine conditions and for performing surgery with computer-assisted surgery systems. The spine has a complex anatomy that consists of 33 vertebrae, 23 intervertebral disks, the ...
First, we relaxed input data requirements found in the literature, and we label both full and partial spine scans. Secondly, we intended to fulfill the performance requirement for daily clinical use and developed a high throughput system capable of processing thousands of slices in just a few ...
Body Type Buttons: This will change the bodypart of the image to the selected value. It is currently available for BRAIN, CSPINE, TSPINE, LSPINE, and ORBITS. Correct Name Button: This will open a form to correct any of the core aspects of the RADIFOX naming convention. extras are not...
A Random Forest classifier labels regions as degenerative change or normal. Leave-one-out cross-validation studies performed on a dataset of 103 patients demonstrates performance of above 95% accuracy. 展开 关键词: Spine X-rays Machine learning Neck ...
Achieved precise segmentation of uterine fibroids and their surrounding organs: The 3D nnU-Net model effectively and accurately segmented the uterus, fibroids, spine, endometrium, bladder, and urethral orifice in early examinations, with Dice Similarity Coefficients of 92.55%, 95.63%, 92.69%, 89.63%,...
(In axial view is the spine at the bottom of the image? In the coronal view is the head at the top of the image?) Other TotalSegmentator sends anonymous usage statistics to help us improve it further. You can deactivate it by setting send_usage_stats to false in ~/.totalsegmentator/...
With the generated jsonl file, a dataset is now ready to be used. However, when mixing all the datasets to train a universal segmentation model, we need toapply normalization on the image intensity, orientation, spacing across all the datasets, and adjust labels if necessary. ...