257 citations · 383 across the 15 of their papers we have counts for
4 papers · 1 filter
Handling Missing MRI Input Data in Deep Learning Segmentation of Brain Metastases: A Multi-Center Study
Endre Grøvik, Darvin Yi, Michael Iv +9
The purpose was to assess the clinical value of a novel DropOut model for detecting and segmenting brain metastases, in which a neural network is trained on four distinct MRI seque…
MRI Pulse Sequence Integration for Deep-Learning Based Brain Metastasis Segmentation
Darvin Yi, Endre Grøvik, Michael Iv +9
Magnetic resonance (MR) imaging is an essential diagnostic tool in clinical medicine. Recently, a variety of deep learning methods have been applied to segmentation tasks in medica…
DeepPerimeter: Indoor Boundary Estimation from Posed Monocular Sequences
Ameya Phalak, Zhao Chen, Darvin Yi +3
We present DeepPerimeter, a deep learning based pipeline for inferring a full indoor perimeter (i.e. exterior boundary map) from a sequence of posed RGB images. Our method relies o…
Deep Learning Enables Automatic Detection and Segmentation of Brain Metastases on Multi-Sequence MRI
Endre Grøvik, Darvin Yi, Michael Iv +3
Detecting and segmenting brain metastases is a tedious and time-consuming task for many radiologists, particularly with the growing use of multi-sequence 3D imaging. This study dem…