John Stuart Haberl Baxter

John Stuart Haberl Baxter
Université de Rennes 1 | UR1 · Laboratoire Traitement du Signal et de l'Image (LTSI) - UMR 1099 Inserm

Professor

About

72
Publications
5,976
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517
Citations
Introduction
John Stuart Haberl Baxter is currently a Chargé de Recherche (Assistant Professor) at L'Equipe MediCIS at the Université de Rennes, where he has worked since completing his doctorate at the Imaging Research Laboratories, Robarts Research Institute. John does research in Biomedical Engineering, Artificial Intelligence and Software Engineering. His publications vary in focus from deep learning, to probabilistic graphical models, to human-computer interaction in machine learning.

Publications

Publications (72)
Article
Purpose: Deep brain stimulation (DBS) is an interventional treatment for some neurological and neurodegenerative diseases. For example, in Parkinson's disease, DBS electrodes are positioned at particular locations within the basal ganglia to alleviate the patient's motor symptoms. These interventions depend greatly on a preoperative planning stage...
Article
Full-text available
Extracting population‐wise information from medical images, specifically in the neurological domain, is crucial to better understanding disease processes and progression. This is frequently done in a whole‐brain voxel‐wise manner, in which a population of patients and healthy controls are registered to a common co‐ordinate space and a statistical t...
Article
Full-text available
Disinhibition is a core symptom of many neurodegenerative diseases, particularly frontotemporal dementia, and is a major cause of stress for caregivers. While a distinction between behavioural and cognitive disinhibition is common, an operational definition of behavioural disinhibition is still missing. Furthermore, conventional assessment of behav...
Preprint
Extracting population-wise information from medical images, specifically in the neurological domain, is crucial to better understanding disease processes and progression. This is frequently done in a whole-brain voxel-wise manner, in which a population of patients and healthy controls are registered to a common co-ordinate space and a statistical t...
Article
Background: Behavioural variant frontotemporal dementia (bvFTD) is partly characterised by inhibition disorders. Neural correlates of disinhibition being poorly known, we aim to identify grey and white matter impairments associated to behavioural disinhibition. Method: We assess behavioural disinhibition in a semi-ecological setting, noting occu...
Article
Full-text available
Deep Brain Stimulation (DBS) is an increasingly common therapy for a large range of neurological disorders, such as abnormal movement disorders. The effectiveness of DBS in terms of controlling patient symptomatology have made this procedure increasingly used over the past few decades. Concurrently, the popularity of Machine Learning (ML), a subfie...
Poster
Full-text available
An ecological approach allows for the identification of two subtypes of behavioural disinhibition: compulsivity and social disinhibition, associated to distinct neural networks. Compulsivity maps the semantic appraisal network while social disinhibition maps the frontal semantic network. https://alz-journals.onlinelibrary.wiley.com/doi/10.1002/alz....
Article
Full-text available
PurposeDeep Brain Stimulation (DBS) is a proven therapy for Parkinson’s Disease (PD), frequently resulting in an enhancement of motor function. Nonetheless, several undesirable side effects can occur after DBS, which can worsen the quality of life of the patient. Thus, the clinical team has to carefully select patients on whom to perform DBS. Over...
Conference Paper
Full-text available
Behavioural variant frontotemporal dementia (bvFTD) is partly characterised by inhibition disorders. Neural correlates of disinhibition being poorly known, we aim to identify white matter bundles associated to behavioural disinhibition. We assess behavioural disinhibition in a semi-ecological setting, noting occurrences of 19 behaviours-derived fro...
Article
Full-text available
PurposeDeep brain stimulation (DBS) is a common treatment for a variety of neurological disorders which involves the precise placement of electrodes at particular subcortical locations such as the subthalamic nucleus. This placement is often guided by auditory analysis of micro-electrode recordings (MERs) which informs the clinical team as to the a...
Article
Full-text available
PurposeTranscranial magnetic stimulation (TMS) is a growing therapy for a variety of psychiatric and neurological disorders that arise from or are modulated by cortical regions of the brain represented by singular 3D target points. These target points are often determined manually with assistance from a pre-operative T1-weighted MRI, although there...
Article
Full-text available
Deep brain stimulation (DBS) is an interventional treatment for Parkinson's disease which involves the precise positioning of stimulated electrodes within deep brain structures, such as the Subthalamic Nucleus (STN). Although originally identified via imaging, additional inter-operative guidance is necessary to localize the target anatomy. Analysis...
Article
Full-text available
Medical questionnaires are a valuable source of information but are often difficult to analyse due to both their size and the high possibility of having missing values. This is a problematic issue in biomedical data science as it may complicate how individual questionnaire data is represented for statistical or machine learning analysis. In this pa...
Conference Paper
Full-text available
Micro-electrode recording (MER) is a powerful way of localizing target structures during neurosurgical procedures such as the implantation of deep brain stimulation electrodes, which is a common treatment for Parkinson's disease and other neurological disorders. While Micro-electrode Recording (MER) provides adjunctive information to guidance assis...
Article
Full-text available
Parkinson’s Disease provokes alterations of subcortical deep gray matter, leading to subtle changes in the shape of several subcortical structures even before the manifestation of motor and non-motor clinical symptoms. We used an automated registration and segmentation pipeline to measure this structural alteration in one early and one advanced Par...
Article
Introduction et but de l’étude Différentes méthodes d’apprentissage peuvent être utilisées pour générer des pseudo-scanographies à partir d’IRM ou de tomographies coniques (cone beam computed tomography, CBCT), permettant un calcul de distribution de dose. L’objectif est d’évaluer des méthodes d’apprentissage pour générer des pseudo-scanographies à...
Article
Objective: To investigate the effects of different positioning on the volume/location of the internal jugular vein (IJV) using 2-dimensional (2D) tracked ultrasound. Design: This was a prospective, observational study. Setting: Local research institute. Participants: Healthy volunteers. Interventions: Twenty healthy volunteers were scanned...
Article
Purpose: Deep learning methods (DLMs) have recently been proposed to generate pseudo-CT (pCT) for MRI-based dose planning. This study aims to evaluate and compare DLMs (U-Net and generative adversarial network (GAN)) using various loss functions (L2, single-scale perceptual loss (PL), multiscale PL, weighted multiscale PL), and a patch-based metho...
Article
Applications of ultrasound guidance for epidural injections are hindered by poor needle and epidural space visualization. This work presents an augmented reality (AR) ultrasound guidance system that addresses challenges in both needle visualization during navigation and epidural space identification for needle positioning. In this system, (i) B-mod...
Article
Purpose To automatically identify regions where prostate cancer is suspected on multi-parametric magnetic resonance images (mp-MRI). Methods A residual network was implemented based on segmentations from an expert radiologist on T2-weighted, apparent diffusion coefficient map, and high b-value diffusion-weighted images. Mp-MRIs from 346 patients w...
Article
Purpose To measure regional specific ventilation with free-breathing hydrogen 1 (1H) magnetic resonance (MR) imaging without exogenous contrast material and to investigate correlations with hyperpolarized helium 3 (3He) MR imaging and pulmonary function test measurements in healthy volunteers and patients with asthma. Materials and Methods Subjects...
Article
As the interaction between clinicians and computational processes increases in complexity, more nuanced mechanisms are required to describe how their communication is mediated. Medical image segmentation in particular affords a large number of distinct loci for interaction which can act on a deep, knowledge-driven level which complicates the naive...
Article
Full-text available
Sensitivity to phase deviations in MRI forms the basis of a variety of techniques including magnetic susceptibility weighted imaging and chemical shift imaging. Current phase processing techniques fall into two families: those which process the complex image data with magnitude and phase coupled, and phase unwrapping based techniques that first lin...
Conference Paper
Periodicity is an important characteristic in many types of video sequences, particularly in medical applications where the cardiac and respiratory cycles are of special significance. Simple spectral analysis or band-pass filtering is often insufficient to extract the periodic signal. Here, we propose modeling the periodic and background components...
Article
Full-text available
Purpose: Real-time ultrasound has become a crucial aspect of several image-guided interventions. One of the main constraints of such an approach is the difficulty in interpretability of the limited field of view of the image, a problem that has recently been addressed using mixed reality, such as augmented reality and augmented virtuality. The gro...
Article
Full-text available
Label ordering, the specification of subset–superset relationships for segmentation labels, has been of increasing interest in image segmentation as they allow for complex regions to be represented as a collection of simple parts. Recent advances in continuous max-flow segmentation have widely expanded the possible label orderings from binary backg...
Article
Full-text available
Ultrasound (US)-guided interventions are often enhanced via integration with an augmented reality environment, a necessary component of which is US calibration. Calibration requires the segmentation of fiducials, i.e., a phantom, in US images. Fiducial localization error (FLE) can decrease US calibration accuracy, which fundamentally affects the to...
Article
Full-text available
Optimization-based segmentation approaches deriving from discrete graph-cuts and continuous max-flow have become increasingly nuanced, allowing for topological and geometric constraints on the resulting segmentation while retaining global optimality. However, these two considerations, topological and geometric, have yet to be combined in a unified...
Article
Interactive segmentation is becoming of increasing interest to the medical imaging community in that it combines the positive aspects of both manual and automated segmentation. However, general-purpose tools have been lacking in terms of segmenting multiple regions simultaneously with a high degree of coupling between groups of labels. Hierarchical...
Article
Full-text available
The incorporation of intensity, spatial, and topological information into large-scale multi-region segmentation has been a topic of ongoing research in medical image analysis. Multi-region segmentation problems, such as segmentation of brain structures, pose unique challenges in image segmentation in which regions may not have a defined intensity,...
Conference Paper
Atrial fibrillation is the most common cardiac arrhythmia and a major cause of ischemic stroke. It is believed that measurements of the thickness of a patient’s left atrial wall can improve understanding of the patient’s disease state, as well as assist in treatment planning for radiofrequency catheter ablation. Left atrial wall thickness can be me...
Conference Paper
Full-text available
Optimization-based segmentation approaches deriving from discrete graph-cuts and continuous max-flow have become increasingly nuanced, allowing for topological and geometric constraints on the resulting segmentation while retaining global optimality. However, these two considerations, topological and geometric, have yet to be combined in a unified...
Conference Paper
Image-based ultrasound to magnetic resonance image (US-MRI) registration can be an invaluable tool in image-guided neuronavigation systems. State-of-the-art commercial and research systems utilize image-based registration to assist in functions such as brain-shift correction, image fusion, and probe calibration. Since traditional US-MRI registratio...
Conference Paper
The removal of the prostate is a common treatment option for localized prostate cancer. Robotic prostatectomy uses endoscopic cameras to provide a stereoscopic view of the surgical scene to the surgeon. Often, this surgical scene is difficult to interpret because of variants in anatomy and some critical structures such as the neurovascular bundles...
Article
Purpose: MRI-based diagnosis of temporal lobe epilepsy (TLE) can be challenging when pathology is not visually evident due to low image contrast or small lesion size. Computer-assisted analyses are able to detect lesions common in a specific patient population, but most techniques do not address clinically relevant individual pathologies resulting...
Article
Full-text available
Reconstruction of an image from noisy data using Markov Random Field theory has been explored by both the graph-cuts and continuous max-flow community in the form of the Potts and Ishikawa models. However, neither model takes into account the particular cyclic topology of specific intensity types such as the hue in natural colour images, or the pha...
Article
Full-text available
Although topological considerations amongst multiple labels have been previously investigated in the context of continuous max-flow image segmentation, similar investigations have yet to be made about shape considerations in a general and extendable manner. This paper presents shape complexes for segmentation, which capture more complex shapes by c...
Conference Paper
Full-text available
Submodular and convex optimization via graph cuts and continuous max-flow have been used extensively as a method for maximum a posteriori estimation in a constrained set of Markov Random Fields and their continuous counterparts. Medical image segmentation has derived a significant amount of value from new formulations that allow for the incorporati...
Conference Paper
Central line procedures are interventions in which a needle is placed in the jugular vein in the patient’s neck inferior to the carotid bifurcation. In these procedures, avoiding the puncture of the carotid artery is of upmost importance as it can cause severe neurological consequences or death. Often, these procedures are performed under ultrasoun...
Conference Paper
We introduce an Iterative Closest Point framework for ultrasound calibration based on a hollow-line phantom. The main novelty of our approach is the application of a hollow-tube fiducial made from hyperechoic material, which allows for highly accurate fiducial localization via both manual and automatic segmentation. By reducing fiducial localizatio...
Article
Epidural and spinal anesthesia are common procedures that require a needle to be inserted into the patient's spine to deliver an anesthetic. Traditionally, these procedures were performed without image guidance, using only palpation to identify the correct vertebral interspace. More recently, ultrasound has seen widespread use in guiding spinal nee...
Article
Several medical imaging modalities exhibit inherent scaling among the acquired data: The scale in an ultrasound image varies with the speed of sound and the scale of the range data used to reconstruct organ surfaces is subject to the scanner distance. In the context of surface-based registration, these scaling factors are often assumed to be isotro...
Conference Paper
Full-text available
Interactive segmentation is becoming of increasing interest to the medical imaging community in that it combines the postive aspects of both manual and automated segmentation. However, general purpose tools have been lacking in terms of segmenting multiple regions simultaneously with a high degree of coupling between groups of labels. Hierarchical...
Conference Paper
Ultrasound calibration is a necessary procedure in many image-guided interventions, relating the position of tools and anatomical structures in the ultrasound image to a common coordinate system. This is a necessary component of augmented reality environments in image-guided interventions as it allows for a 3D visualization where other surgical too...
Article
The primary purpose of medical image visualization is to improve patient outcomes by facilitating the inspection, analysis, and interpretation of patient data. This is only possible if the users’ perceptual and cognitive limitations are taken into account during every step of design, implementation, and evaluation of interactive displays. Visualiza...
Article
Full-text available
One issue limiting the adaption of large-scale multi-region segmentation is the sometimes prohibitive memory requirements. This is especially troubling considering advances in massively parallel computing and commercial graphics processing units because of their already limited memory compared to the current random access memory used in more tradit...
Conference Paper
We propose a new principle, the variational region competition, to simultaneously propagate multiple disjoint level-sets in a fully time-implicit manner, minimizing the total cost w.r.t. region changes. We demonstrate, that the problem of multiphase level-set evolution can be reformulated in terms of a Potts problem, for which fast optimization alg...
Article
Full-text available
Planning surgical interventions is a complex task, demanding a high degree of perceptual, cognitive, and sensorimotor skills to reduce intra- and postoperative complications. This process requires spatial reasoning to coordinate between the preoperatively acquired medical images and patient reference frames. In the case of neurosurgical interventio...
Article
In addition to coil sensitivity data (parallel imaging), sparsity constraints are often used as an additional lp-penalty for under-sampled MRI reconstruction (compressed sensing). Penalizing the traditional decimated wavelet transform (DWT) coefficients, however, results in visual pseudo-Gibbs artifacts, some of which are attributed to the lack of...
Article
Full-text available
The incorporation of region regularization into max-flow segmentation has traditionally focused on ordering and part-whole relationships. A side effect of the development of such models is that it constrained regularization only to those cases, rather than allowing for arbitrary region regularization. Directed Acyclic Graphical Max-Flow (DAGMF) seg...
Article
Full-text available
Optimization techniques have been widely used in deformable registration, allowing for the incorporation of similarity metrics with regularization mechanisms. These regularization mechanisms are designed to mitigate the effects of trivial solutions to ill-posed registration problems and to otherwise ensure the resulting deformation fields are well-...
Article
Full-text available
Multi-region segmentation algorithms often have the onus of incorporating complex anatomical knowledge representing spatial or geometric relationships between objects, and general-purpose methods of addressing this knowledge in an optimization-based manner have thus been lacking. This paper presents Generalized Hierarchical Max-Flow (GHMF) segmenta...
Conference Paper
Full-text available
Simultaneous segmentation of multiple anatomical objects from medical images has become of increasing interest to the medical imaging community, especially when information concerning these objects such as grouping or hierarchical relationships can facilitate segmentation. Single parameter Potts models have often been used to address these multi-re...
Conference Paper
Endoscopic and laparoscopic surgeries are used for many minimally invasive procedures but limit the visual and haptic feedback available to the surgeon. This can make vessel sparing procedures particularly challenging to perform. Previous approaches have focused on hardware intensive intraoperative imaging or augmented reality systems that are diff...
Conference Paper
Ultrasound calibration allows for ultrasound images to be incorporated into a variety of interventional applica­ tions. Traditional Z- bar calibration procedures rely on wired phantoms with an a priori known geometry. The line fiducials produce small, localized echoes which are then segmented from an array of ultrasound images from different tracke...
Article
This study investigates a method for brain tissue segmentation from 3D T1 weighted (T1w) MR images via convex relaxation with a hierarchical ordering constraint. It employs a multi-atlas-based initialization from 5 training images and is tested on 12 T1w MR images provided by the MICCAI 2013 MRBrainS segmentation challenge. The registered atlas ima...
Conference Paper
The lack of intuitive visualization techniques for neurosurgical planning is a challenging hurdle faced by neurosurgeons and neurosurgery residents. Within this context, this paper describes the development and evaluation of an Augmented Reality (AR) system geared towards planning brain tumour resection interventions. Successful resection of a tumo...
Chapter
The environment in which a surgeons is trained profoundly effects their preferred method for visualizing patient images. While classical 2D viewing might be preferred by some older experts, the new generation of residents and novices has been raised navigating in 3D through video games, and are accustomed to seeing 3D reconstructions of the human a...