3 papers
eess.IV2024
Multi-task Learning To Improve Semantic Segmentation Of CBCT Scans Using Image Reconstruction
Maximilian Ernst Tschuchnig, Julia Coste-Marin, Philipp Steininger +1
Semantic segmentation is a crucial task in medical image processing, essential for segmenting organs or lesions such as tumors. In this study we aim to improve automated segmentati…
eess.IV2024
Evaluation of Multi-Scale Multiple Instance Learning to Improve Thyroid Cancer Classification
Maximilian E. Tschuchnig, Philipp Grubmüller, Lea M. Stangassinger +5
Thyroid cancer is currently the fifth most common malignancy diagnosed in women. Since differentiation of cancer sub-types is important for treatment and current, manual methods ar…
eess.IV2024
Anomaly Detection in Medical Imaging -- A Mini Review
Maximilian E. Tschuchnig, Michael Gadermayr
The increasing digitization of medical imaging enables machine learning based improvements in detecting, visualizing and segmenting lesions, easing the workload for medical experts…