activity
20172022
most citedTeCNO: Surgical Phase Recognition with Multi-Stage Temporal Convolutional Networks

232 citations · 278 across the 15 of their papers we have counts for

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Showing 2020Show all

7 papers · 1 filter

eess.IV2020★ 7 cited

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…

cs.CV2020★ 4 cited

Efficient Ensemble Model Generation for Uncertainty Estimation with Bayesian Approximation in Segmentation

Hong Joo Lee, Seong Tae Kim, Hakmin Lee +2

Recent studies have shown that ensemble approaches could not only improve accuracy and but also estimate model uncertainty in deep learning. However, it requires a large number of…

cs.CV2020★ 1 cited

Robust Ensemble Model Training via Random Layer Sampling Against Adversarial Attack

Hakmin Lee, Hong Joo Lee, Seong Tae Kim +1

Deep neural networks have achieved substantial achievements in several computer vision areas, but have vulnerabilities that are often fooled by adversarial examples that are not re…

cs.CV2020★ 2 cited

Confident Coreset for Active Learning in Medical Image Analysis

Seong Tae Kim, Farrukh Mushtaq, Nassir Navab

Recent advances in deep learning have resulted in great successes in various applications. Although semi-supervised or unsupervised learning methods have been widely investigated,…

eess.IV2020★ 1 cited

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…

eess.IV2020★ 232 cited

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…

eess.IV2020

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…