10 citations · 25 across the 7 of their papers we have counts for
6 papers · 1 filter
Improved Abdominal Multi-Organ Segmentation via 3D Boundary-Constrained Deep Neural Networks
Samra Irshad, Douglas P. S. Gomes, Seong Tae Kim
Quantitative assessment of the abdominal region from clinically acquired CT scans requires the simultaneous segmentation of abdominal organs. Thanks to the availability of high-per…
Longitudinal Quantitative Assessment of COVID-19 Infection Progression from Chest CTs
Seong Tae Kim, Leili Goli, Magdalini Paschali +7
Chest computed tomography (CT) has played an essential diagnostic role in assessing patients with COVID-19 by showing disease-specific image features such as ground-glass opacity a…
Self-Supervised Out-of-Distribution Detection in Brain CT Scans
Abinav Ravi Venkatakrishnan, Seong Tae Kim, Rami Eisawy +2
Medical imaging data suffers from the limited availability of annotation because annotating 3D medical data is a time-consuming and expensive task. Moreover, even if the annotation…
Spatio-temporal Learning from Longitudinal Data for Multiple Sclerosis Lesion Segmentation
Stefan Denner, Ashkan Khakzar, Moiz Sajid +4
Segmentation of Multiple Sclerosis (MS) lesions in longitudinal brain MR scans is performed for monitoring the progression of MS lesions. We hypothesize that the spatio-temporal cu…
TeCNO: Surgical Phase Recognition with Multi-Stage Temporal Convolutional Networks
Tobias Czempiel, Magdalini Paschali, Matthias Keicher +4
Automatic surgical phase recognition is a challenging and crucial task with the potential to improve patient safety and become an integral part of intra-operative decision-support…
Force-Ultrasound Fusion: Bringing Spine Robotic-US to the Next "Level"
Maria Tirindelli, Maria Victorova, Javier Esteban +4
Spine injections are commonly performed in several clinical procedures. The localization of the target vertebral level (i.e. the position of a vertebra in a spine) is typically don…