Validation of automated lobe segmentation on paired inspiratory-expiratory chest CT in 8-14 year-old children with cystic fibrosis | PLOS ONE
![Robust deep 3-D architectures based on vascular patterns for liver vessel segmentation - ScienceDirect Robust deep 3-D architectures based on vascular patterns for liver vessel segmentation - ScienceDirect](https://ars.els-cdn.com/content/image/1-s2.0-S2352914822002489-gr1.jpg)
Robust deep 3-D architectures based on vascular patterns for liver vessel segmentation - ScienceDirect
Multi-perspective label based deep learning framework for cerebral vasculature segmentation in whole-brain fluorescence images
![Imaging of the pial arterial vasculature of the human brain in vivo using high-resolution 7T time-of-flight angiography | eLife Imaging of the pial arterial vasculature of the human brain in vivo using high-resolution 7T time-of-flight angiography | eLife](https://iiif.elifesciences.org/lax/71186%2Felife-71186-fig6-figsupp2-v2.tif/full/1500,/0/default.jpg)
Imaging of the pial arterial vasculature of the human brain in vivo using high-resolution 7T time-of-flight angiography | eLife
![Frontiers | DeepVesselNet: Vessel Segmentation, Centerline Prediction, and Bifurcation Detection in 3-D Angiographic Volumes Frontiers | DeepVesselNet: Vessel Segmentation, Centerline Prediction, and Bifurcation Detection in 3-D Angiographic Volumes](https://www.frontiersin.org/files/Articles/592352/fnins-14-592352-HTML/image_m/fnins-14-592352-g001.jpg)
Frontiers | DeepVesselNet: Vessel Segmentation, Centerline Prediction, and Bifurcation Detection in 3-D Angiographic Volumes
![Using deep learning for a diffusion-based segmentation of the dentate nucleus and its benefits over atlas-based methods | Medical-image Analysis and Statistical Interpretation (MASI) Lab | Vanderbilt University Using deep learning for a diffusion-based segmentation of the dentate nucleus and its benefits over atlas-based methods | Medical-image Analysis and Statistical Interpretation (MASI) Lab | Vanderbilt University](https://my.vanderbilt.edu/masi/files/2019/12/dentate.png)
Using deep learning for a diffusion-based segmentation of the dentate nucleus and its benefits over atlas-based methods | Medical-image Analysis and Statistical Interpretation (MASI) Lab | Vanderbilt University
![AngioNet: a convolutional neural network for vessel segmentation in X-ray angiography | Scientific Reports AngioNet: a convolutional neural network for vessel segmentation in X-ray angiography | Scientific Reports](https://media.springernature.com/m685/springer-static/image/art%3A10.1038%2Fs41598-021-97355-8/MediaObjects/41598_2021_97355_Fig1_HTML.png)
AngioNet: a convolutional neural network for vessel segmentation in X-ray angiography | Scientific Reports
![CMM-Net: Contextual multi-scale multi-level network for efficient biomedical image segmentation | Scientific Reports CMM-Net: Contextual multi-scale multi-level network for efficient biomedical image segmentation | Scientific Reports](https://media.springernature.com/full/springer-static/image/art%3A10.1038%2Fs41598-021-89686-3/MediaObjects/41598_2021_89686_Fig1_HTML.png)
CMM-Net: Contextual multi-scale multi-level network for efficient biomedical image segmentation | Scientific Reports
![SynthSR: A public AI tool to turn heterogeneous clinical brain scans into high-resolution T1-weighted images for 3D morphometry | Science Advances SynthSR: A public AI tool to turn heterogeneous clinical brain scans into high-resolution T1-weighted images for 3D morphometry | Science Advances](https://www.science.org/cms/10.1126/sciadv.add3607/asset/f006810b-5ff3-4034-a144-00b49132fbcb/assets/images/large/sciadv.add3607-f1.jpg)
SynthSR: A public AI tool to turn heterogeneous clinical brain scans into high-resolution T1-weighted images for 3D morphometry | Science Advances
![Automatic vessel segmentation in X-ray angiogram using spatio-temporal fully-convolutional neural network - ScienceDirect Automatic vessel segmentation in X-ray angiogram using spatio-temporal fully-convolutional neural network - ScienceDirect](https://ars.els-cdn.com/content/image/1-s2.0-S1746809421002433-gr1.jpg)