Active Contour-Based Segmentation of Head and Neck with Adaptive Atlas Selection

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

There are many approaches to weakly-supervised training of networks to segment 2D images. By contrast, existing approaches to segmenting volumetric images rely on full-supervision of a subset of 2D slices of the 3D volume. We propose an approach to volume ...

Large training datasets have played a vital role in the success of modern deep learning methods in computer vision. But, obtaining sufficient amount of training data is challenging, specially when annotating volumetric images. This is because fully annotat ...

Human-centered scene understanding is the process of perceiving and analysing a dynamic scene observed through a network of sensors with emphasis on human-related activities. It includes the visual perception of human-related activities from either single ...

Attribute-based representations help machine learning models perform tasks based on human understandable concepts, allowing a closer human-machine collaboration. However, learning attributes that accurately reflect the content of an image is not always str ...

Determining the relationship between the cause of damage and the subsequent structural behavior of infrastructure systems requires an accurate characterization of the propagation of cracks, which represents the evolution of the damage state. When no inform ...

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 ...

Background The relationship between osteoporosis and intervertebral disc (IVD) degeneration remains controversial. Novel quantitative Dixon (Q-Dixon) and GRAPPATINI T2 mapping techniques have shown potential for evaluating the biochemical components of the ...

The acquisition of high quality maps of gene expression in the rodent brain is of fundamental importance to the neuroscience community. The generation of such datasets relies on registering individual gene expression images to a reference volume, a task en ...

Objectives Fluid and white matter suppression (FLAWS) is a recently proposed magnetic resonance sequence derived from magnetization-prepared 2 rapid acquisition gradient-echo providing 2 coregistered datasets with white matter- and cerebrospinal fluid-supp ...

Background and objective: Compared to the conventional magnetization-prepared rapid gradient-echo imaging (MPRAGE) MRI sequence, the specialized magnetization prepared 2 rapid acquisition gradient echoes (MP2RAGE) shows a higher brain tissue and lesion con ...

During the Artificial Intelligence (AI) revolution of the past decades, deep neural networks have been widely used and have achieved tremendous success in visual recognition. Unfortunately, deploying deep models is challenging because of their huge model s ...

Molecular medical imaging is intended to increase the accuracy of diagnosis, particularly in cardiovascular and cancer-related diseases, where early detection could significantly increase the treatment success rate. In this study, we present mixed micelles ...

Purpose: T1 Magnetization Prepared Two Rapid Acquisition Gradient Echo (MP2RAGE) with compress sensing (CS) has been proposed as an improvement of the standard MPRAGE sequence with multiple advantages including reduced acquisition time needed to provide a ...

Spectral imaging is a fundamental diagnostic technique with widespread application. Conventional spectral imaging approaches have intrinsic limitations on spatial and spectral resolutions due to the physical components they rely on. To overcome these physi ...

Single-molecule imaging methods are of importance in structural biology, and specifically in the imaging of proteins, since they can elucidate conformational variability and structural changes that might be lost in imaging methods relying on averaging proc ...

We address the detection, tracking, and relative localization of the agents of a drone swarm from a human perspective using a headset equipped with a single camera and an Inertial Measurement Unit (IMU). We train and deploy a deep neural network detector o ...

Multiple sclerosis (MS) is the most common demyelinating disease of the central nervous system and affects almost 3 million people worldwide. There is currently no cure for MS, and its symptoms, starting with fatigue and weakness, often progress over time ...

The present invention concerns an array processing image reconstruction method comprising: receiving (13) a set of echo waveforms as measurements from the object of interest; defining (15) a measurement model linking an unknown image of the object to the m ...

The accurate identification of the three-dimensional quantitative shape of a cell nucleus is now possible without fluorescent staining by applying computational segmentation to refractive index tomograms recorded in the flow cytometry mode. ...

Active Contour-Based Segmentation of Head and Neck with Adaptive Atlas Selection

Chat with Graph Search

Weakly Supervised Volumetric Image Segmentation with Deformed Templates

Object Priors for Volumetric Image Segmentation

Human-Centered Scene Understanding via Crowd Counting

Attribute Prediction as Multiple Instance Learning

Determining crack kinematics from imaged crack patterns

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

Q-Dixon and GRAPPATINI T2 Mapping Parameters: A Whole Spinal Assessment of the Relationship Between Osteoporosis and Intervertebral Disc Degeneration

Supervised Learning With Perceptual Similarity for Multimodal Gene Expression Registration of a Mouse Brain Atlas

3-Dimensional Fluid and White Matter Suppression Magnetic Resonance Imaging Sequence Accelerated With Compressed Sensing Improves Multiple Sclerosis Cervical Spinal Cord Lesion Detection Compared With Standard 2-Dimensional Imaging

MPRAGE to MP2RAGE UNI translation via generative adversarial network improves the automatic tissue and lesion segmentation in multiple sclerosis patients

Improving the Training of Compact Neural Networks for Visual Recognition

Vascular-targeted micelles as a specific MRI contrast agent for molecular imaging of fibrin clots and cancer cells

Compressed sensing (CS) MP2RAGE versus standard MPRAGE: A of derived brain volume measurements

High-Resolution Multi-Spectral Imaging With Diffractive Lenses and Learned Reconstruction

Amplitude and phase reconstruction for Low-Energy Electron Holography of individual proteins

Tracking and Relative Localization of Drone Swarms With a Vision-Based Headset

Deep learning-based analysis of multiple sclerosis lesions with high and ultra-high field MRI

Image reconstruction method based on a trained non-linear mapping

Stain-free identification of cell nuclei using tomographic phase microscopy in flow cytometry