13 citations · 16 across the 6 of their papers we have counts for
6 papers
Content-based 3D Image Retrieval and a ColBERT-inspired Re-ranking for Tumor Flagging and Staging
Farnaz Khun Jush, Steffen Vogler, Matthias Lenga
The increasing volume of medical images poses challenges for radiologists in retrieving relevant cases. Content-based image retrieval (CBIR) systems offer potential for efficient a…
Content-Based Image Retrieval for Multi-Class Volumetric Radiology Images: A Benchmark Study
Farnaz Khun Jush, Steffen Vogler, Tuan Truong +1
While content-based image retrieval (CBIR) has been extensively studied in natural image retrieval, its application to medical images presents ongoing challenges, primarily due to…
Benchmarking Pretrained Vision Embeddings for Near- and Duplicate Detection in Medical Images
Tuan Truong, Farnaz Khun Jush, Matthias Lenga
Near- and duplicate image detection is a critical concern in the field of medical imaging. Medical datasets often contain similar or duplicate images from various sources, which ca…
Medical Image Retrieval Using Pretrained Embeddings
Farnaz Khun Jush, Tuan Truong, Steffen Vogler +1
A wide range of imaging techniques and data formats available for medical images make accurate retrieval from image databases challenging. Efficient retrieval systems are crucial i…
AutoSpeed: A Linked Autoencoder Approach for Pulse-Echo Speed-of-Sound Imaging for Medical Ultrasound
Farnaz Khun Jush, Markus Biele, Peter M. Dueppenbecker +1
Quantitative ultrasound, e.g., speed-of-sound (SoS) in tissues, provides information about tissue properties that have diagnostic value. Recent studies showed the possibility of ex…
Deep Learning for Ultrasound Speed-of-Sound Reconstruction: Impacts of Training Data Diversity on Stability and Robustness
Farnaz Khun Jush, Markus Biele, Peter M. Dueppenbecker +1
Ultrasound b-mode imaging is a qualitative approach and diagnostic quality strongly depends on operators' training and experience. Quantitative approaches can provide information a…