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Chapter
Conference Paper
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Image Processing and Computer Vision
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Chapter and Conference Paper
Keynote: Recent Advances in Surgical AI for Next Generation Interventions
Recent trends in Artificial Intelligence (AI) and surgical science have revolutionized the field of surgery, paving the way for a new era of AI-assisted robotic interventions. These cutting-edge technologies o...
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Chapter and Conference Paper
Correction to: Vision Transformers for Breast Cancer Histology Image Classification
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Chapter and Conference Paper
Abstract: Deep Learning-based Detection of Vessel Occlusions on CT-Angiography in Patients with Suspected Acute Ischemic Stroke
Swift diagnosis and treatment play a decisive role in the clinical outcome of patients with acute ischemic stroke (AIS), and computer-aided diagnosis (CAD) systems can accelerate the underlying diagnostic proc...
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Chapter and Conference Paper
Abstract: Adaptive Region Selection for Active Learning in Whole Slide Image Semantic Segmentation
The annotation of gigapixel-sized whole slide images (WSI) in digital pathology can be time-intensive, especially when generating annotations for training deep segmentation models. Instead of requesting annota...
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Chapter and Conference Paper
Abstract: Interpretable Medical Image Classification Using Prototype Learning and Privileged Information
Interpretability is often an essential requirement in medical imaging. Advanced deep learning methods are required to address this need for explainability and high performance. In this work, we investigate whe...
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Chapter and Conference Paper
Abstract: Metal-conscious Embedding for CBCT Projection Inpainting
The existence of metallic implants in projection images for cone-beam computed tomography (CBCT) introduces undesired artifacts which degrade the quality of reconstructed images. In order to reduce metal artif...
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Chapter and Conference Paper
Abstract: Object Detection for Breast Diffusion-weighted Imaging
Diffusion-weighted imaging (DWI) is a rapidly emerging unenhanced MRI technique in oncologic breast imaging. This IRB approved study included n=818 patients (with n=618 malignant lesions in n=268 patients). Al...
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Chapter and Conference Paper
Abstract: Enhanced Diagnostic Fidelity in Pathology Whole Slide Image Compression via Deep Learning
Accurate diagnosis of disease often depends on the exhaustive examination of whole slide images (WSI) at microscopic resolution. Efficient handling of these data-intensive images requires lossy compression tec...
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Chapter and Conference Paper
Abstract: Metal Inpainting in CBCT Projections using Score-based Generative Model
During orthopaedic surgery, the insertion of metallic implants or screws is often performed under mobile C-arm systems. However, due to the high attenuation of metals, severe metal artifacts occur in 3D recons...
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Chapter and Conference Paper
Abstract: Transient Hemodynamics Prediction using an Efficient Octree-based Deep Learning Model
Patient-specific hemodynamics assessment has the potential to support diagnosis and treatment of neurovascular diseases. Currently, conventional medical imaging modalities are not able to accurately acquire hi...
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Chapter and Conference Paper
Abstract: Focused Unsupervised Image Registration for Structure-specific Population Analysis
Population-based analysis of medical images plays an essential role in identification and development of imaging biomarkers. Most commonly the focus lies on a single structure or image region in order to ident...
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Chapter and Conference Paper
Abstract: Multi-dataset Approach to Medical Image Segmentation
The medical imaging community generates a wealth of data-sets, many of which are openly accessible and annotated for specific diseases and tasks such as multi-organ or lesion segmentation. Current practices co...
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Chapter and Conference Paper
Abstract: Spatiotemporal Illumination Model for 3D Image Fusion in Optical Coherence Tomography
Optical coherence tomography (OCT) is a non-invasive, micrometer-scale imaging modality that has become a clinical standard in ophthalmology. By raster-scanning the retina, sequential cross-sectional image sli...
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Chapter and Conference Paper
Abstract: Enabling Geometry Aware Learning Through Differentiable Epipolar View Translation
Epipolar geometry is exploited in several applications in the field of Cone-Beam Computed Tomography (CBCT) imaging. By leveraging consistency conditions between multiple views of the same scene, motion artifa...
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Chapter and Conference Paper
Abstract: Baseline Pipeline for Automated Eye Redness Extraction with Relation to Clinical Grading
An essential bio-marker to detect ocular surface diseases like dry eye disease is ocular redness. In clinical routine, this marker is graded by visual comparison to reference image scales. We aim at supporting...
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Chapter and Conference Paper
Abstract: RecycleNet
Despite the remarkable success of deep learning systems over the last decade, a key difference still remains between neural network and human decision-making: As humans, we can not only form a decision on the ...
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Chapter and Conference Paper
Abstract: Advancing Large-scale Deformable 3D Registration with Differentiable Volumetric Rasterisation of Point Clouds
3D point clouds are an efficient and privacy-preserving representation of medical scans highly suitable for complex segmentation and registration tasks. Yet, current loss functions for training self-supervised...
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Chapter and Conference Paper
Abstract: Reformulating COPD Classification on Chest CT Scans as Anomaly Detection using Contrastive Representations
Classification of heterogeneous diseases is challenging due to their complexity, variability of symptoms and imaging findings. Chronic obstructive pulmonary disease (COPD) is a prime example, being underdiagno...
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Chapter and Conference Paper
Increasing Accessibility of Online Board Games to Visually Impaired People via Machine Learning and Textual/Audio Feedback: The Case of “Quantik”
Playing board games is commonly recognized as an effective way to promote the integration and socialization of their participants. However, visually impaired people may encounter accessibility issues when play...
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Chapter and Conference Paper
Abstract: Comprehensive Multi-domain Dataset for Mitotic Figure Detection
The density of mitotic figures is a well-established diagnostic marker for tumor malignancy across many tumor types and species. At the same time, the identification of mitotic figures in hematoxylin and eosin...
