Paul S Babyn

• Saskatchewan Health Authority

Low‐dose computed tomography (CT) images are prone to noise and artifacts caused by photon starvation and electronic noise. Recently, researchers have explored the use of transformer‐based neural networks combined with generative diffusion models, showing promising results in denoising CT images. Despite their high performance, these approaches oft...

CT image denoising is a crucial task in medical imaging systems, aimed at enhancing the quality of acquired visual signals. The emergence of diffusion models in machine learning has revolutionized the generation of high-quality CT images. However, diffusion-based CT image denoising methods suffer from two key shortcomings. First, they do not incorp...

X-ray computed tomography (CT) is vital for medical diagnostics, but frequent radiation exposure raises concerns, driving the adoption of low-dose CT (LDCT) to mitigate risks. However, LDCT often introduces noise, compromising diagnostic accuracy. This paper proposes a pure vision transformer (PViT) for LDCT denoising, enhanced with a gradient–Lapl...

Convolutional neural networks (CNN) have been used for a wide variety of deep learning applications, especially in computer vision. For medical image processing, researchers have identified certain challenges associated with CNNs. These challenges encompass the generation of less informative features, limitations in capturing both high and low-freq...

Deep learning techniques have made its way to the medical field. Medical images are essential tools for visualizing internal body structures up to cellular levels. X-ray computed tomography (CT) is a widely used non-invasive medical modality for patient diagnosis. Harmful effects of cumulative amounts of radiation exposure to patients undergoing CT...

Computed tomography (CT) stands as a pivotal medical imaging technique, delivering timely and reliable clinical evaluations. Yet, its dependence on ionizing radiation raises health concerns. One mitigation strategy involves using reduced radiation for low-dose CT (LDCT) imaging; however, this often results in noise artifacts that undermine diagnost...

Objective: Neonatal catheters and tubes are commonly used for monitoring and support for intensive care and must be correctly positioned to avoid complications. Position assessment is routinely done by radiography. The objective of this study is to characterize neonatal catheter and tube placement in terms of the proportion of those devices that a...

Purpose: Medical imaging can be used to estimate a patient's biological age, which may provide complementary information to clinicians compared to chronological age. In this study, we aimed to develop a method to estimate a patient's age based on their chest CT scan. Additionally, we investigated whether chest CT estimated age is a more accurate p...

Osteonecrosis (ON) is a serious complication of childhood acute lymphoblastic leukemia. We determined the prevalence of osteonecrotic lesions in our patient population by a one-time multi-site magnetic resonance imaging (MRI) more than one year following leukemia therapy. MRI findings were evaluated in relationship to clinical factors (including lo...

Purpose: The usage of iodinated contrast media (ICM) can improve the sensitivity and specificity of computed tomography (CT) for many clinical indications. However, the adverse effects of ICM administration can include renal injury, life-threatening allergic-like reactions, and environmental contamination. Deep learning (DL) models can generate fu...

Conventional Endoscopy (CE) and Wireless Capsule Endoscopy (WCE) are well known tools for diagnosing gastrointestinal (GI) tract related disorders. Defining the anatomical location within the GI tract helps clinicians determine appropriate treatment options, which can reduce the need for repetitive endoscopy. Limited research addresses the localiza...

This research paper explores the use of ChatGPT in database management. ChatGPT, an AI-powered chatbot, has limitations in performing tasks related to database management due to the lack of standardized vocabulary and grammar for representing database semantics. To address this limitation, the paper proposes a solution that involves developing a se...

This paper proposes a new scheduling problem for patient visits with two objectives: minimizing patient waiting time and travel time. It also presents a novel encoding method for Genetic Algorithms (GA) that is well-suited for this problem. Experiments demonstrate that the proposed encoding method reduces optimization iterations by 17% compared to...

Morquio syndrome, also known as Morquio-Brailsford syndrome or mucopolysaccharidosis type IV (MPS IV), is a subgroup of mucopolysaccharidosis. It is an autosomal recessive lysosomal storage disorder. Two subtypes of Morquio syndrome have been identified. In MPS IVA, a deficiency in N-acetylgalactosamine-6-sulfate sulfatase interrupts the normal met...

Objective To evaluate whether an imaging classifier for radiology practice can improve lung nodule classification and follow-up. Methods A machine learning classifier was developed and trained using imaging data from the National Lung Screening Trial (NSLT) to produce a malignancy risk score (mSI) for individual lung nodules. In addition to NLST c...

Introduction: Telerobotic ultrasound technology allows radiologists and sonographers to remotely provide ultrasound services in underserved areas. This study aimed to compare costs associated with using telerobotic ultrasound to provide ultrasound services in rural and remote communities to costs associated with alternate models. Methods: A cost...

With the increasing concern regarding the radiation exposure of patients undergoing computed tomography (CT) scans, researchers have been using deep learning techniques to improve the quality of denoised low-dose CT (LDCT) images. In this paper, a cascaded dilated residual network (ResNet) with integrated attention modules, specifically spatial- an...

Deep learning techniques have emerged in de-noising low-dose computed tomography (CT) images to avoid the potential health risks of high ionizing radiation dose on patients. Although these post-processing methods display high quality denoised images, the denoising performance still has the potential to improve. The primary purpose of this work was...

Most artificial intelligence (AI) studies have focused primarily on adult imaging, with less attention to the unique aspects of pediatric imaging. The objectives of this study were to (1) identify all publicly available pediatric datasets and determine their potential utility and limitations for pediatric AI studies and (2) systematically review th...

X-ray computed tomography (CT) is a non-invasive medical diagnostic tool that has raised public concerns due to the associated health risks of radiation dose to patients. Reducing the radiation dose leads to noise artifacts, making the low-dose CT images unreliable for diagnosis. Hence, low-dose CT (LDCT) image reconstruction techniques have offere...

Purpose of the program: Nîsohkamâtowak, the Cree word for Helping Each Other, is an initiative to close gaps in kidney health care for First Nations and Métis patients, their families, and communities in northern Saskatchewan. Nîsohkamâtowak emerged from a collaboration between the Kidney Health Community Program and First Nations and Métis Health...

Objective Patients living in many rural and remote areas do not have readily available access to ultrasound services because of a lack of sonographers and radiologists in these communities. The objective of this study was to determine the feasibility of using telerobotic ultrasound to establish a service delivery model to remotely provide access to...

CT machines can be tuned in order to reduce the radiation dose used for imaging, yet reducing the radiation dose results in noisy images which are not suitable in clinical practice. In order for low dose CT to be used effectively in practice this issue must be addressed. Generative Adversarial Networks (GAN) have been used widely in computer vision...

Image denoising of Low-dose computed tomography (LDCT) images has continues to receive attention in the research community due to ongoing concerns about high-dose radiation exposure of patients for diagnosis. The use of low radiation CT image, however, could lead to inaccurate diagnosis due to the presence of noise. Deep learning techniques are bei...

Objective Ultrasound is one of the most commonly used imaging modalities, though some populations face barriers in accessing ultrasound services, potentially resulting in disparities in utilization. The objective of this study was to assess the association between sociodemographic and geographic factors and non-obstetrical ultrasound utilization in...

Background: This study examined the structural outcomes for joints of boys with severe hemophilia A receiving frequency/dose-escalated primary prophylaxis using magnetic resonance imaging (MRI), and the importance of interval MRI changes. Methods: Forty-six subjects (27 with interval studies) were evaluated by radiographs (X-rays) and mid- and e...

ABSTRACT Ultrasound imaging is an essential component of healthcare services. This study sought to explore perceptions of access, and factors which shape access, to ultrasound imaging in two northern, remote, Indigenous communities in Canada. Using interpretive description as a meth- odological approach and a multi-dimensional conceptualisation of...

Rationale and Objectives Obstetrical ultrasound imaging is an important part of prenatal care, though not all patients have readily available access to ultrasound services. This study aimed to assess the association between sociodemographic and geographic factors and (1) having a second trimester complete obstetrical ultrasound and (2) overall obst...

Wireless Capsule Endoscopy (WCE) helps physicians examine the gastrointestinal (GI) tract noninvasively. There are few studies that address pathological assessment of endoscopy images in multiclass classification and most of them are based on binary anomaly detection or aim to detect a specific type of anomaly. Multiclass anomaly detection is chall...

The incidence of oropharyngeal squamous cell carcinoma (OPSCC) is rising sharply. The aim of this meta-analysis is to evaluate the prognostic value of PET/CT radiomics parameters in oropharyngeal carcinoma patients. A comprehensive literature search was carried out through five libraries from inception until 17 May 2018. We extracted an estimate of...

Introduction For persons with hemophilia, optimization of joint outcomes is an important unmet need. The aim of this initiative was to determine use of ultrasound in evaluating arthropathy in persons with hemophilia, and to move toward consensus among hemophilia care providers regarding the preferred ultrasound protocols for global adaptation. Met...

We develop and evaluate a deep learning algorithm to classify multiple catheters on neonatal chest and abdominal radiographs. A convolutional neural network (CNN) was trained using a dataset of 777 neonatal chest and abdominal radiographs, with a split of 81%–9%–10% for training-validation-testing, respectively. We employed ResNet-50 (a CNN), pre-t...

Conventional Endoscopy (CE) and Wireless Capsule Endoscopy (WCE) are known tools for diagnosing gastrointestinal (GI) tract disorders. Localizing frames provide valuable information about the anomaly location and also can help clinicians determine a more appropriate treatment plan. There are many automated algorithms to detect the anomaly. However,...

Objectives To develop a lung nodule management strategy combining the Lung CT Screening Reporting and Data System (Lung-RADS) with an artificial intelligence (AI) malignancy risk score and determine its impact on follow-up investigations and associated costs in a baseline lung cancer screening population. Materials and Methods Secondary analysis w...

Lung cancer is a leading cause of cancer death in Canada, and accurate, early diagnosis are critical to improving clinical outcomes. Artificial Intelligence (AI)-based imaging analytics are a promising healthcare innovation that aim to improve the accuracy and efficiency of lung cancer diagnosis. Maximizing their clinical potential while mitigating...

Purpose: 1. To review the contemporary literature and present a list of the imaging findings for patients with autoinflammatory diseases from our hospital. All these patients are found to have a genetic mutation that is responsible for their disease. 2. To present follow-up imaging findings, when available, and correlate those with symptoms and ty...

We develop and evaluate a deep learning algorithm to classify multiple catheters on neonatal chest and abdominal radiographs. A convolutional neural network (CNN) was trained using a dataset of 777 neonatal chest and abdominal radiographs, with a split of 81%-9%-10% for training-validation-testing, respectively. We employed ResNet-50 (a CNN), pre-t...

Introduction: Obstetrical ultrasound imaging is critical in identifying at-risk pregnancies and informing clinical management. The coronavirus disease 2019 (COVID-19) pandemic has exacerbated challenges in accessing obstetrical ultrasound for patients in underserved rural and remote communities where this service is not available. This prospective...

Access to sonographers and sonologists is limited in many communities around the world. Telerobotic sonography (robotic ultrasound) is a new technology to increase access to sonography, providing sonographers and sonologists the ability to manipulate an ultrasound probe from a distant location and remotely perform ultrasound examinations. This narr...

In the early months of the COVID-19 pandemic with no designated cure or vaccine, the only way to break the infection chain is self-isolation and maintaining the physical distancing. In this article, we present a potential application of the Internet of Things (IoT) in healthcare and physical distance monitoring for pandemic situations. The proposed...

Objectives: Obstetrical ultrasound imaging is critical in identifying at-risk pregnancies and informing clinical management. The COVID-19 pandemic has exacerbated challenges in accessing obstetrical ultrasound for patients in underserved rural and remote communities where this service is not available. The objective of this study is to assess the f...

Artificial intelligence (AI) presents a key opportunity for radiologists to improve quality of care and enhance the value of radiology in patient care and population health. The potential opportunity of AI to aid in triage and interpretation of conventional radiographs (X-ray images) is particularly significant, as radiographs are the most common i...

Low Dose CT Denoising research aims to reduce the risks of radiation exposure to patients. Recently researchers have used deep learning to denoise low dose CT images with promising results. However, approaches that use mean-squared-error (MSE) tend to over smooth the image resulting in loss of fine structural details in low contrast regions of the...

Low-Dose Computed Tomography (LDCT) has yet to get its full potential benefit due to excessive quantum noise. Although learning to restore an image using two noisy images in Noise2noise (N2N) model has shown good promise for different noise models, it does not perform well in LDCT. In this paper, we have introduced a collaborative technique to trai...

Aim The objective of this survey was to understand the global trends of imaging assessments in persons with haemophilia, focusing on point‐of‐care ultrasound (POCUS). Insights into the barriers impeding its widespread proliferation as a frontline imaging modality were obtained. Methods The survey opened in September of 2017 and closed in May of 20...

Catheters are the second most common abnormal finding on radiographs. The position of catheters must be assessed on all radiographs, as serious complications can arise if catheters are malpositioned. However, due to the large number of radiographs performed each day, there can be substantial delays between the time a radiograph is performed and whe...

Ultrasound can penetrate deep into tissues and interact with human tissue via thermal and mechanical mechanisms. The ability to focus an ultrasound beam and its energy onto millimeter-size targets was a significant milestone in the development of therapeutic applications of focused ultrasound. Focused ultrasound can be used as a non-invasive therma...

A model was developed for long term metformin tissue retention based upon temporally inclusive models of serum/plasma concentration (C) having power function tails called the gamma-Pareto type I convolution (GPC) model and was contrasted with biexponential (E2) and noncompartmental (NC) metformin models. GPC models of C have a peripheral venous fir...

Catheters are the second most common abnormal finding on radiographs. The position of catheters must be assessed on all radiographs because serious complications can arise if catheters are malpositioned. However, due to the large number of radiographs obtained each day, there can be substantial delays between the time a radiograph is obtained and w...

Covering both pediatric and adult populations, this comprehensive text covers the diverse topics related to the health, disease and therapy of articular cartilage of the knee, from basic principles to future directions for research. This vast array of information is arranged into eight sections, encompassing a number of relevant disciplines and cov...

Health care-associated infections (HCAIs) are a significant concern for both health care workers (HCWs) and patients. They are a major contributing factor of disease in industrialized countries, and are responsible for significant morbidity, mortality, and a direct annual financial loss of $6-7 billion in North America alone. They are an increasing...

Low-dose CT denoising is a challenging task that has been studied by many researchers. Some studies have used deep neural networks to improve the quality of low-dose CT images and achieved fruitful results. In this paper, we propose a deep neural network that uses dilated convolutions with different dilation rates instead of standard convolution he...

Generative adversarial networks have gained a lot of attention in the computer vision community due to their capability of data generation without explicitly modelling the probability density function. The adversarial loss brought by the discriminator provides a clever way of incorporating unlabeled samples into training and imposing higher order c...

Low-dose CT imaging is a valid approach to reduce patients' exposure to X-ray radiation. However, reducing X-ray current increases noise and artifacts in the reconstructed CT images. Deep neural networks have been successfully employed to remove noise from low-dose CT images. This study proposes two novel techniques to boost the performance of a ne...

Computer-aided diagnosis (CAD) has already been widely used in medical image processing. We recently make another trial to implement convolutional neural network (CNN) on the classification of pulmonary nodules of thoracic CT images. The biggest challenge in medical image classification with the help of CNN is the difficulty of acquiring enough sam...

The challenges and barriers associated with the provision of healthcare and access to imaging in a remote, northern, community.

A summary of current technologies being used to perform and capture remotely generated ultrasound images. The telerobotic abilities of the different systems are compared.

LEARNING OBJECTIVES: 1. Describe how telerobotic ultrasound systems enable sonographers to remotely perform ultrasound examinations and enable radiologists reading off-site to remotely scan to confirm findings; 2. Discuss clinical applications of telerobotic sonography, and review clinical studies evaluating the feasibility and diagnostic accuracy...

PURPOSE: Access to medical imaging remains limited for many people across the world in both developing and developed countries. This study sought to explore perceptions of access, and factors which shape access, to ultrasound imaging in two neighboring northern, remote Indigenous communities in Canada. METHOD AND MATERIALS: Semi-structured intervi...

Low-dose CT denoising is a challenging task that has been studied by many researchers. Some studies have used deep neural networks to improve the quality of low-dose CT images and achieved fruitful results. In this paper, we propose a deep neural network that uses dilated convolutions with different dilation rates instead of standard convolution he...

Purpose To develop and evaluate the reliability of an explicit set of parameters and criteria for simple bone cysts (SBCs) and evaluate the reliability of single versus serial chronological reading methods Methods Radiographic criteria were developed based on the literature and expert consensus. A single anteroposterior/lateral radiograph from 32...

Background Elevated brain iron has been observed in Idiopathic Parkinson's disease (IPD) within the deep gray matter. Using quantitative susceptibility mapping (QSM) and a thresholded high-iron region, we quantified iron content in the midbrain of patients with Parkinson's disease as a function of age. Methods We used MRI to scan 24 IPD patients a...

High-resolution synchrotron computed tomography (CT) is very helpful in the diagnosis and monitor of chronic diseases including osteoporosis. Osteoporosis is characterized by low bone mass and cortical bone porosity best imaged with CT. Synchrotron CT requires a large number of angular projections to reconstruct images with high resolution for deta...

Objectives: Concerns about unnecessary medical imaging have led to the development of guidelines for a variety of indications and modalities by radiology and specialty groups. This study evaluates the utility of four national imaging guidelines, which assess the value of positron emitting tomography/computed tomography (PET/CT). As PET/CT is an eme...

Low-dose Computed Tomography (CT) is considered a solution for reducing the risk of X-ray radiation; however, lowering the X-ray current results in a degraded reconstructed image. To improve the quality of the image, different noise removal techniques have been proposed. Con- volutional neural networks also have shown promising results in denoising...

Catheters are commonly inserted life supporting devices. X-ray images are used to assess the position of a catheter immediately after placement as serious complications can arise from malpositioned catheters. Previous computer vision approaches to detect catheters on X-ray images either relied on low-level cues that are not sufficiently robust or o...

Background Endometriosis affects one in ten women of reproductive age but it is diagnosed at advanced stages. Our objective was to develop a domestic animal model that would permit sequential assessment of endometriotic changes. Materials and methods Surgical transplantation of endometrial tissue and fat (n = 4 grafts/tissue/animal) was done in do...

Background: Severe haemophilia A has high morbidity, and treatment, while effective, is very expensive. We report the 16-year follow-up of the Canadian Hemophilia Prophylaxis Study, which examined the effectiveness of tailored frequency-escalated primary prophylaxis with a focus on health outcomes within the domains of body structures and function...

Objectives: To determine the feasibility of a telerobotic approach to remotely perform prenatal sonographic examinations. Methods: Thirty participants were prospectively recruited. Participants underwent a limited examination (assessing biometry, placental location, and amniotic fluid; n = 20) or a detailed examination (biometry, placental locat...

Purpose To evaluate the hypothesis that power-injectable totally implanted venous access devices (TIVADs) situated in the arm are associated with more frequent complications and complication-related removal than non–power-injectable arm TIVADs among adult cancer patients. Materials and Methods In this single-center trial, 211 adult chemotherapy p...

Over the past decades, different techniques have been investigated for detecting microbubbles. The purpose of this work is to review the state-of-the-art of medical microbubble detection along with therapeutic, monitoring, and diagnostic applications. The presence of microbubbles in the human body can be induced either through cavitation or exogeno...

Melanoma is a curable aggressive skin cancer if detected early. Typically, the diagnosis involves initial screening with subsequent biopsy and histopathological examination if necessary. Computer aided diagnosis offers an objective score that is independent of clinical experience and the potential to lower the workload of a dermatologist. In the re...

Artificial intelligence (AI) is rapidly moving from an experimental phase to an implementation phase in many fields, including medicine. The combination of improved availability of large datasets, increasing computing power, and advances in learning algorithms has created major performance breakthroughs in the development of AI applications. In the...

In order to reduce radiation effect during CT scans, low-dose techniques are employed in different medical imaging applications. But images in the low-dose CT tend to be rather noisy to be diagnostically useful. One way to improve the quality of low-dose CT images is to use a multi-frame imaging technique. Here we proposed a blind source separation...

Biofabrication of cell supportive cardiac patches that can be directly implanted on myocardial infarct is a potential solution for myocardial infarction repair. Ideally, cardiac patches should be able to mimic myocardium extracellular matrix for rapid integration with the host tissue, raising the need to develop cardiac constructs with complex feat...

Purpose: The study sought to determine the incidence of incidental findings on whole-body positron emission tomography with computed tomography (PET/CT) imaging and the average costs of investigations to follow-up or further characterize incidental findings. Methods: Imaging reports of 215 patients who underwent whole-body PET/CT imaging were re...

PURPOSE To determine the feasibility of using a telerobotic ultrasound system to remotely perform prenatal ultrasound examinations and generate images of diagnostic quality, and determine the acceptability of the system to patients and sonographers. METHOD AND MATERIALS Thirty participants (mean gestational age 22.8 weeks, range 15-36 weeks) were p...

An essential objective in medical low-dose Computed Tomography (CT) imaging is how best to preserve the quality of the image. While, reducing the X-ray radiation dose is desired, in general, the image quality lowers by reducing the dose. Therefore, improving image quality is remarkably crucial for diagnostic purposes. A novel method to denoise low-...