1 citations · 1 across the 16 of their papers we have counts for
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Sharing standardized image-derived data in computational pathology using DICOM
Daniela P. Schacherer, Christopher P. Bridge, David Clunie +13
Development and evaluation of computational pathology methods require access to large and diverse datasets. Over the past decade, various initiatives invested significantly into co…
CONFLUX: A Latent Diffusion Model for 3D Chest-CT Synthesis with RL Post-Training
Max Van Puyvelde, Halil Ibrahim Gulluk, Wim Van Criekinge +1
Controllable generative models of 3D medical images can synthesize volumes with specified clinical attributes, but this demands samples that are simultaneously high-fidelity, nativ…
JASPR: Joint Spatial Representation learning of histology and spatial genomics for improved virtual genomic screening and clinical prognostication
Marija Pizurica, Eric Zimmermann, Neil Tenenholtz +5
Recent studies have shown that spatial properties of tumors are critical for understanding disease biology and predicting patient outcomes. These spatial properties are increasingl…
Transition-Aware best-of-N sampling for Longitudinal Chest X-ray Reports
Halil Ibrahim Gulluk, Max Van Puyvelde, Wim Van Criekinge +1
In longitudinal clinical practice, every chest X-ray is read in the context of the patients prior exam, and much of what the radiologist communicates is the change from one visit t…
MAM-CLIP: Vision-Language Pretraining on Mammography Atlases for BI-RADS Classification
Halil Ibrahim Gulluk, Olivier Gevaert
Deep learning methods have demonstrated promising results in predicting BI-RADS scores from mammography images. However, the interpretation of these images can vary, leading to dis…
Prior Knowledge Injection into Deep Learning Models Predicting Gene Expression from Whole Slide Images
Max Hallemeesch, Marija Pizurica, Paloma Rabaey +3
Cancer diagnosis and prognosis primarily depend on clinical parameters such as age and tumor grade, and are increasingly complemented by molecular data, such as gene expression, fr…