A spreadsheet framework for medical visualization

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Volume electron microscopy is the method of choice for the in situ interrogation of cellular ultrastructure at the nanometer scale, and with the increase in large raw image datasets generated, improving computational strategies for image segmentation and s ...

Recent advancements in deep learning have revolutionized 3D computer vision, enabling the extraction of intricate 3D information from 2D images and video sequences. This thesis explores the application of deep learning in three crucial challenges of 3D com ...

Dataflow programming is a methodology that enables the development of high-level, parametric programs that are independent of the underlying platform. This approach is particularly useful for heterogeneous platforms, as it eliminates the need to rewrite ap ...

Today's continued increase in demand for processing power, despite the slowdown of Moore's law, has led to an increase in processor count, which has resulted in energy consumption and distribution problems. To address this, there is a growing trend toward ...

Histology is a long standing and well-established gold standard for pathological characterizations. In recent years however, synchrotron radiation-based micro-computed tomography (SR mu CT) has become a tool for extending the imaging of two-dimensional thi ...

Physically based rendering methods can create photorealistic images by simulating the propagation and interaction of light in a virtual scene. Given a scene description including the shape of objects, participating media, material properties, etc., the sim ...

Writing and optimizing application software for heterogeneous platforms including GPU units is a very difficult task that requires designer efforts and resources to consider several key elements to obtain good performance. Dataflow programming has shown to ...

The performance of programs executed on heterogeneous parallel platforms largely depends on the design choices regarding how to partition the processing on the various different processing units. In other words, it depends on the assumptions and parameters ...

Physically based rendering is a process for photorealistic digital image synthesis and one of the core problems in computer graphics. It involves simulating the light transport, i.e. the emission, propagation, and scattering of light through a virtual scen ...

Modern information technologies and human-centric communication systems employ advanced content representations for richer portrayals of the real world. The newly adopted imaging modalities offer additional information cues and permit the depiction of real ...

Despite the successes of deep neural networks on many challenging vision tasks, they often fail to generalize to new test domains that are not distributed identically to the training data. The domain adaptation becomes more challenging for cross-modality m ...

We introduce a novel transmittance model to improve the volumetric representation of 3D scenes. The model can represent opaque surfaces in the volumetric light transport framework. Volumetric representations are useful for complex scenes, and become increa ...

Physically based differentiable rendering algorithms propagate derivatives through realistic light transport simulations and have applications in diverse areas including inverse reconstruction and machine learning. Recent progress has led to unbiased metho ...

Physically based differentiable rendering has recently evolved into a powerful tool for solving inverse problems involving light. Methods in this area perform a differentiable simulation of the physical process of light transport and scattering to estimate ...

Realistic rendering using discrete reflectance measurements is challenging, because arbitrary directions on the light and view hemispheres are queried at render time, incurring large memory requirements and the need for interpolation. This explains the des ...

The difficulty of obtaining annotations to build training databases still slows down the adoption of recent deep learning approaches for biomedical image analysis. In this paper, we show that we can train a Deep Net to perform 3D volumetric delineation giv ...

This study aimed to explore the value of synchrotron-based phase-contrast microcomputed tomography (micro-CT) in pulmonary vascular pathobiology. The microanatomy of the lung is complex with intricate branching patterns. Tissue sections are therefore diffi ...

Omnidirectional imaging has reached a level of widespread availability driven by recent advances in integrated circuit technology, image sensors, and computer graphics which allow now capturing, rendering and displaying of such type of immersive content in ...

Since its invention in the 19th century, photography has allowed to create durable images of the world around us by capturing the intensity of light that flows through a scene, first analogically by using light-sensitive material, and then, with the advent ...

Quality assessment of light field images poses new questions and challenges, due to the enriched nature of the content and the possibilities it offers at the rendering step. Image-based rendering is conventionally used to showcase the increased capabilitie ...

A spreadsheet framework for medical visualization

Chat with Graph Search

Modular segmentation, spatial analysis and visualization of volume electron microscopy datasets

Advancing Self-Supervised Deep Learning for 3D Scene Understanding

Design Space Exploration for Partitioning Dataflow Program on CPU-GPU Heterogeneous System

Compilation and Design Space Exploration of Dataflow Programs for Heterogeneous CPU-GPU Platforms

Sub-micrometer morphology of human atherosclerotic plaque revealed by synchrotron radiation-based mu CT-A comparison with histology

Differentiable Physically Based Rendering: Algorithms, Systems and Applications

SIMD Parallel Execution on GPU from High-Level Dataflow Synthesis

Performance Estimation of High-Level Dataflow Program on Heterogeneous Platforms by Dynamic Network Execution

Light Path Gradients for Forward and Inverse Rendering

Perceptual Quality of Point Clouds with application to Compression

Self-Attentive Spatial Adaptive Normalization for Cross-Modality Domain Adaptation

A Non-Exponential Transmittance Model for Volumetric Scene Representations

Monte Carlo Estimators for Differential Light Transport

Radiative Backpropagation: An Adjoint Method for Lightning-Fast Differentiable Rendering

Unified Neural Encoding of BTFs

Tracing in 2D to reduce the annotation effort for 3D deep delineation of linear structures

Synchrotron-based phase-contrast micro-CT as a tool for understanding pulmonary vascular pathobiology and the 3-D microanatomy of alveolar capillary dysplasia

Visual Attention and Perceptual Quality in Omnidirectional Imaging

Compression and visual quality assessment for light field contents

An in-depth analysis of single-image subjective quality assessment of light field contents