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20132020
most citedA Contrast-Adaptive Method for Simultaneous Whole-Brain and Lesion Segmentation in Multiple Sclerosis

164 citations

Showing 2018Show all

5 papers · 1 filter

cs.CV2018

Learning to quantify emphysema extent: What labels do we need?

Silas Nyboe Ørting, Jens Petersen, Laura H. Thomsen +2

Accurate assessment of pulmonary emphysema is crucial to assess disease severity and subtype, to monitor disease progression and to predict lung cancer risk. However, visual assess…

cs.CV2018★ 1 cited

Deep Learning from Label Proportions for Emphysema Quantification

Gerda Bortsova, Florian Dubost, Silas Ørting +5

We propose an end-to-end deep learning method that learns to estimate emphysema extent from proportions of the diseased tissue. These proportions were visually estimated by experts…

cs.CV2018

Feature learning based on visual similarity triplets in medical image analysis: A case study of emphysema in chest CT scans

Silas Nyboe Ørting, Jens Petersen, Veronika Cheplygina +3

Supervised feature learning using convolutional neural networks (CNNs) can provide concise and disease relevant representations of medical images. However, training CNNs requires a…

physics.med-ph2018

The value of ultrahigh resolution OCT in dermatology - delineating the dermo-epidermal junction, capillaries in the dermal papillae and vellus hairs

Niels Møller Israelsen, Michael Maria, Mette Mogensen +5

Optical coherence tomography (OCT) imaging of the skin is gaining recognition and is increasingly applied to dermatological research. A key dermatological parameter inferred from a…

physics.med-ph2018

Two Optical Coherence Tomography Systems detect Topical Gold Nanoparticles in Hair follicles, Sweat Ducts and Measure Epidermis

Mette Mogensen, Sophie Bojesen, Niels Israelsen +5

Optical coherence tomography (OCT) is an established imaging technology for in vivo skin investigation. Topical application of gold nanoshells (GNS) provides contrast enhancement i…