347 citations · 1.3k across the 70 of their papers we have counts for
14 papers · 1 filter
Self-supervised learning-based cervical cytology for the triage of HPV-positive women in resource-limited settings and low-data regime
Thomas Stegmüller, Christian Abbet, Behzad Bozorgtabar +4
Screening Papanicolaou test samples has proven to be highly effective in reducing cervical cancer-related mortality. However, the lack of trained cytopathologists hinders its wides…
Cortical lesions, central vein sign, and paramagnetic rim lesions in multiple sclerosis: emerging machine learning techniques and future avenues
Francesco La Rosa, Maxence Wynen, Omar Al-Louzi +11
The current multiple sclerosis (MS) diagnostic criteria lack specificity, and this may lead to misdiagnosis, which remains an issue in present-day clinical practice. In addition, c…
Validation and Generalizability of Self-Supervised Image Reconstruction Methods for Undersampled MRI
Thomas Yu, Tom Hilbert, Gian Franco Piredda +8
Deep learning methods have become the state of the art for undersampled MR reconstruction. Particularly for cases where it is infeasible or impossible for ground truth, fully sampl…
Multi-compartment diffusion MRI, T2 relaxometry and myelin water imaging as neuroimaging descriptors for anomalous tissue detection
Elda Fischi-Gomez, Jonathan Rafael-Patino, Marco Pizzolato +5
Multiple sclerosis (MS) is an inflammatory and neurodegenerative disease characterized by diffuse and focal areas of tissue loss. Conventional MRI techniques such as T1-weighted an…
Anomaly Detection on X-Rays Using Self-Supervised Aggregation Learning
Behzad Bozorgtabar, Dwarikanath Mahapatra, Guillaume Vray +1
Deep anomaly detection models using a supervised mode of learning usually work under a closed set assumption and suffer from overfitting to previously seen rare anomalies at traini…
CNN-Based Ultrasound Image Reconstruction for Ultrafast Displacement Tracking
Dimitris Perdios, Manuel Vonlanthen, Florian Martinez +2
Thanks to its capability of acquiring full-view frames at multiple kilohertz, ultrafast ultrasound imaging unlocked the analysis of rapidly changing physical phenomena in the human…
Automated Detection of Cortical Lesions in Multiple Sclerosis Patients with 7T MRI
Francesco La Rosa, Erin S Beck, Ahmed Abdulkadir +4
The automated detection of cortical lesions (CLs) in patients with multiple sclerosis (MS) is a challenging task that, despite its clinical relevance, has received very little atte…
CNN-Based Image Reconstruction Method for Ultrafast Ultrasound Imaging
Dimitris Perdios, Manuel Vonlanthen, Florian Martinez +2
Ultrafast ultrasound (US) revolutionized biomedical imaging with its capability of acquiring full-view frames at over 1 kHz, unlocking breakthrough modalities such as shear-wave el…
Structure Preserving Stain Normalization of Histopathology Images Using Self-Supervised Semantic Guidance
Dwarikanath Mahapatra, Behzad Bozorgtabar, Jean-Philippe Thiran +1
Although generative adversarial network (GAN) based style transfer is state of the art in histopathology color-stain normalization, they do not explicitly integrate structural info…
T2 Mapping from Super-Resolution-Reconstructed Clinical Fast Spin Echo Magnetic Resonance Acquisitions
Hélène Lajous, Tom Hilbert, Christopher W. Roy +12
Relaxometry studies in preterm and at-term newborns have provided insight into brain microstructure, thus opening new avenues for studying normal brain development and supporting d…
Divide-and-Rule: Self-Supervised Learning for Survival Analysis in Colorectal Cancer
Christian Abbet, Inti Zlobec, Behzad Bozorgtabar +1
With the long-term rapid increase in incidences of colorectal cancer (CRC), there is an urgent clinical need to improve risk stratification. The conventional pathology report is us…
Benefiting from Bicubically Down-Sampled Images for Learning Real-World Image Super-Resolution
Mohammad Saeed Rad, Thomas Yu, Claudiu Musat +3
Super-resolution (SR) has traditionally been based on pairs of high-resolution images (HR) and their low-resolution (LR) counterparts obtained artificially with bicubic downsamplin…
Pathological Retinal Region Segmentation From OCT Images Using Geometric Relation Based Augmentation
Dwarikanath Mahapatra, Behzad Bozorgtabar, Jean-Philippe Thiran +1
Medical image segmentation is an important task for computer aided diagnosis. Pixelwise manual annotations of large datasets require high expertise and is time consuming. Conventio…
Fast Fiber Orientation Estimation in Diffusion MRI from kq-Space Sampling and Anatomical Priors
Marica Pesce, Audrey Repetti, Anna Auría +3
High spatio-angular resolution diffusion MRI (dMRI) has been shown to provide accurate identification of complex neuronal fiber configurations, albeit, at the cost of long acquisit…