7 papers
Hybrid Deep Learning and Handcrafted Feature Fusion for Mammographic Breast Cancer Classification
Maximilian Tschuchnig, Michael Gadermayr, Khalifa Djemal
Automated breast cancer classification from mammography remains a significant challenge due to subtle distinctions between benign and malignant tissue. In this work, we present a h…
Enhancing Synthetic CT from CBCT via Multimodal Fusion and End-To-End Registration
Maximilian Tschuchnig, Lukas Lamminger, Philipp Steininger +1
Cone-Beam Computed Tomography (CBCT) is widely used for intraoperative imaging due to its rapid acquisition and low radiation dose. However, CBCT images typically suffer from artif…
Enhancing Synthetic CT from CBCT via Multimodal Fusion: A Study on the Impact of CBCT Quality and Alignment
Maximilian Tschuchnig, Lukas Lamminger, Philipp Steininger +1
Cone-Beam Computed Tomography (CBCT) is widely used for real-time intraoperative imaging due to its low radiation dose and high acquisition speed. However, despite its high resolut…
Initial Study On Improving Segmentation By Combining Preoperative CT And Intraoperative CBCT Using Synthetic Data
Maximilian E. Tschuchnig, Philipp Steininger, Michael Gadermayr
Computer-Assisted Interventions enable clinicians to perform precise, minimally invasive procedures, often relying on advanced imaging methods. Cone-beam computed tomography (CBCT)…
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…
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…