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15 papers · 1 filter
Potential and challenges of generative adversarial networks for super-resolution in 4D Flow MRI
Oliver Welin Odeback, Arivazhagan Geetha Balasubramanian, Jonas Schollenberger +9
4D Flow Magnetic Resonance Imaging (4D Flow MRI) enables non-invasive quantification of blood flow and hemodynamic parameters. However, its clinical application is limited by low s…
WEEP: A method for spatial interpretation of weakly supervised CNN models in computational pathology
Abhinav Sharma, Bojing Liu, Mattias Rantalainen
Deep learning enables the modelling of high-resolution histopathology whole-slide images (WSI). Weakly supervised learning of tile-level data is typically applied for tasks where l…
Pre- to Post-Contrast Breast MRI Synthesis for Enhanced Tumour Segmentation
Richard Osuala, Smriti Joshi, Apostolia Tsirikoglou +4
Despite its benefits for tumour detection and treatment, the administration of contrast agents in dynamic contrast-enhanced MRI (DCE-MRI) is associated with a range of issues, incl…
A novel framework employing deep multi-attention channels network for the autonomous detection of metastasizing cells through fluorescence microscopy
Michail Mamalakis, Sarah C. Macfarlane, Scott V. Notley +2
We developed a transparent computational large-scale imaging-based framework that can distinguish between normal and metastasizing human cells. The method relies on fluorescence mi…
On undesired emergent behaviors in compound prostate cancer detection systems
Erlend Sortland Rolfsnes, Philip Thangngat, Trygve Eftestøl +4
Artificial intelligence systems show promise to aid in the di- agnostic pathway of prostate cancer (PC), by supporting radiologists in interpreting magnetic resonance images (MRI)…
The ACROBAT 2022 Challenge: Automatic Registration Of Breast Cancer Tissue
Philippe Weitz, Masi Valkonen, Leslie Solorzano +38
The alignment of tissue between histopathological whole-slide-images (WSI) is crucial for research and clinical applications. Advances in computing, deep learning, and availability…