30 citations · 45 across the 5 of their papers we have counts for
7 papers
Representing Ambiguity in Registration Problems with Conditional Invertible Neural Networks
Darya Trofimova, Tim Adler, Lisa Kausch +5
Image registration is the basis for many applications in the fields of medical image computing and computer assisted interventions. One example is the registration of 2D X-ray imag…
Invertible Neural Networks for Uncertainty Quantification in Photoacoustic Imaging
Jan-Hinrich Nölke, Tim Adler, Janek Gröhl +5
Multispectral photoacoustic imaging (PAI) is an emerging imaging modality which enables the recovery of functional tissue parameters such as blood oxygenation. However, the underly…
Heidelberg Colorectal Data Set for Surgical Data Science in the Sensor Operating Room
Lena Maier-Hein, Martin Wagner, Tobias Ross +30
Image-based tracking of medical instruments is an integral part of surgical data science applications. Previous research has addressed the tasks of detecting, segmenting and tracki…
Out of distribution detection for intra-operative functional imaging
Tim J. Adler, Leonardo Ayala, Lynton Ardizzone +6
Multispectral optical imaging is becoming a key tool in the operating room. Recent research has shown that machine learning algorithms can be used to convert pixel-wise reflectance…
Photoacoustic monitoring of blood oxygenation during neurosurgical interventions
Thomas Kirchner, Janek Gröhl, Niklas Holzwarth +5
Multispectral photoacoustic (PA) imaging is a prime modality to monitor hemodynamics and changes in blood oxygenation (sO2). Although sO2 changes can be an indicator of brain activ…
Uncertainty-aware performance assessment of optical imaging modalities with invertible neural networks
Tim J. Adler, Lynton Ardizzone, Anant Vemuri +8
Purpose: Optical imaging is evolving as a key technique for advanced sensing in the operating room. Recent research has shown that machine learning algorithms can be used to addres…