Browsing Faculty of Engineering by subject "0801 Artificial Intelligence and Image Processing"
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Adaptive path planning for depth‐constrained bathymetric mapping with an autonomous surface vessel
Published 2017-01-01This paper describes the design, implementation, and testing of a suite of algorithms to enable depth‐constrained autonomous bathymetric (underwater topography) mapping by an autonomous surface vessel (ASV). Given a target ...Article -
Adversarial Recurrent Time Series Imputation
Published 2020For the real-world time series analysis, data missing is a ubiquitously existing problem due to anomalies during data collecting and storage. If not treated properly, this problem will seriously hinder the classification, ...Open AccessArticle -
Bounding Drift in Cooperative Localisation Through the Sharing of Local Loop Closures
Published 2018-01-01Handling loop closures and intervehicle observations in cooperative robotic scenarios remains a challenging problem due to data consistency, bandwidth limitations and increased computation requirements. This paper develops ...Article -
Characterization of the Intel RealSense D415 Stereo Depth Camera for Motion-Corrected CT Imaging
Published 2019A combination of non-contrast CT (NCCT) and CT Perfusion (CTP) imaging is the most common regime for evaluation of acute ischemic stroke patients. CTP-based image analysis is known to be compromised by patient head motion. ...Open AccessConference paper -
Close-range feature-based head motion tracking for MRI and PET-MRI
Published 2018Optical motion tracking systems are effective in measuring head motion during MRI and PET scans. However, most systems rely on tracking attached markers which can slip or move relative to the head. In this study, we aimed ...Open AccessConference paper -
Deep learning-based motion estimation for uninterrupted tracking of awake rodents in PET
Published 2018The ability to image the brain of awake rodents using motion-compensated positron emission tomography (PET) presents many exciting possibilities for exploring the links between brain function and behavior. A key requirement ...Open AccessConference paper -
Dual-Path Adversarial Learning for Fully Convolutional Network (FCN)-Based Medical Image Segmentation
Published 2018-01-01Segmentation of regions of interest (ROIs) in medical images is an important step for image analysis in computer-aided diagnosis systems. In recent years, segmentation methods based on fully convolutional networks (FCNs) ...Open AccessArticle -
Feasibility of marker-free motion tracking for motion-corrected MRI and PET-MRI
Published 2016Prospective motion correction is a very promising compensation approach for magnetic resonance imaging (MRI) studies impacted by motion. It has the advantage over retrospective methods of being applicable to any pulse ...Open AccessConference paper -
Iterative Privileged Learning
Published 2020While in the learning using privileged information paradigm, privileged information may not be as informative as example features in the context of making accurate label predictions, it may be able to provide some effective ...Open AccessArticle -
Long-Term Video Prediction via Criticization and Retrospection
Published 2020Video prediction refers to predicting and generating future video frames given a set of consecutive frames. Conventional video prediction methods usually criticize the discrepancy between the ground-truth and predictions ...Open AccessArticle -
Marker-free optical stereo motion tracking for in-bore MRI and PET-MRI application
Published 2020Purpose: Prospective motion correction is arguably the “silver bullet” solution for magnetic resonance imaging (MRI) studies impacted by motion, applicable to almost any pulse sequence and immune from the spin history ...Open AccessArticle -
Markerless motion estimation for motion-compensated clinical brain imaging
Published 2018Motion-compensated brain imaging can dramatically reduce the artifacts and quantitative degradation associated with voluntary and involuntary subject head motion during positron emission tomography (PET), single photon ...Open AccessArticle -
Multi-Label Classification of Multi-Modality Skin Lesion via Hyper-Connected Convolutional Neural Network
Published 2020-01-01Objective: Clinical and dermoscopy images (multi-modality image pairs) are routinely used sequentially in the assessment of skin lesions. Clinical images characterize a lesion’s geometry and color; dermoscopy depicts ...Open AccessArticle -
Multi-task Learning for Blind Source Separation
Published 2018Blind source separation (BSS) aims to discover the underlying source signals from a set of linear mixture signals without any prior information of the mixing system, which is a fundamental problem in signal and image ...Open AccessArticle -
Multimodal learning and inference from visual and remotely sensed data
Published 2016-01-01Autonomous vehicles are often tasked to explore unseen environments, aiming to acquire and understand large amounts of visual image data and other sensory information. In such scenarios, remote sensing data may be available ...Article -
Non-rigid motion detection for motion tracking of the head
Published 2019Optical motion tracking systems are effective tools for measuring head motion during MRI and PET scans in order to correct for motion. Most systems rely on the attachment of fiducial markers which can slip or become decoupled ...Open AccessConference paper -
Open-field PET: Simultaneous brain functional imaging and behavioural response measurements in freely moving small animals
Published 2019A comprehensive understanding of how the brain responds to a changing environment requires techniques capable of recording functional outputs at the whole-brain level in response to external stimuli. Positron emission tomography ...Open AccessArticle -
An optimized feature detector for markerless motion tracking in motion-compensated neuroimaging
Published 2017Head movements during PET and MRI scans can have a detrimental effect on image quality and quantitative measurements. For both modalities, motion correction methods exist that rely on accurate characterization of head ...Open AccessConference paper -
Packing Convolutional Neural Networks in the Frequency Domain
Published 2019Deep convolutional neural networks (CNNs) are successfully used in a number of applications. However, their storage and computational requirements have largely prevented their widespread use on mobile devices. Here we ...Open AccessArticle -
Recurrent Feature Fusion Learning for Multi-Modality PET-CT Tumor Segmentation
Published 2021Background and Objective: [18F]-Fluorodeoxyglucose (FDG) positron emission tomography – computed tomography (PET-CT) is now the preferred imaging modality for staging many cancers. PET images characterize tumoral glucose ...Open AccessArticle