A5085553444- AI in cancer detection
- Brain Tumor Detection and Classification
- Medical Imaging Techniques and Applications
- Radiomics and Machine Learning in Medical Imaging
- COVID-19 diagnosis using AI
- Digital Imaging for Blood Diseases
- Advanced MRI Techniques and Applications
- Medical Image Segmentation Techniques
- Advanced Neural Network Applications
- Chemical Reactions and Isotopes
- Artificial Intelligence in Healthcare and Education
- Advanced X-ray and CT Imaging
- Artificial Intelligence in Healthcare
- Global Cancer Incidence and Screening
- Cervical Cancer and HPV Research
- Cell Image Analysis Techniques
Lawson Health Research Institute
2023-2025
McGill University
2024
Western University
2023-2024
“Just Accepted” papers have undergone full peer review and been accepted for publication in Radiology: Artificial Intelligence. This article will undergo copyediting, layout, proof before it is published its final version. Please note that during production of the copyedited article, errors may be discovered which could affect content. The BraTS-Africa Dataset first annotated publicly available brain imaging dataset from an African population. It contains three-dimensional MRI scans,...
Gliomas are the most common type of primary brain tumors. Although gliomas relatively rare, they among deadliest types cancer, with a survival rate less than 2 years after diagnosis. challenging to diagnose, hard treat and inherently resistant conventional therapy. Years extensive research improve diagnosis treatment have decreased mortality rates across Global North, while chances individuals in low- middle-income countries (LMICs) remain unchanged significantly worse Sub-Saharan Africa...
Cerebral blood flow and blood-brain barrier permeability assessment are crucial hemodynamic parameters to measure under neurological conditions. In conjunction with positron emission tomography (PET), oxygen-15-labeled water has emerged as a gold standard for measuring cerebral perfusion; however, at higher rates, [
In Positron Emission Tomography (PET) imaging, the use of tracers increases radioactive exposure for longitudinal evaluations and in radiosensitive populations such as pediatrics. However, reducing injected PET activity potentially leads to an unfavorable compromise between radiation image quality, causing lower signal-to-noise ratios degraded images. Deep learning-based denoising approaches can be employed recover low count signals: nonetheless, most these methods rely on structural or...
Automating brain tumor segmentation using deep learning methods is an ongoing challenge in medical imaging. Multiple lingering issues exist including domain-shift and applications low-resource settings which brings a unique set of challenges scarcity data. As step towards solving these specific problems, we propose Convolutional adapter-inspired Parameter-efficient Fine-tuning (PEFT) MedNeXt architecture. To validate our idea, show method performs comparable to full fine-tuning with the...
The last decade has seen an increase in the application of machine learning (ML) methods to PET/MRI attenuation correction (AC). This systematic review provides a head-to-head comparison between state-of-the-art ML and clinical standards for AC determine feasibility approaches PET AC. We extracted numerical values image quality, tissue classification, regional global diagnostic performance. pooled mean relative error performance was 0.87 ± 1.3%, quality evidence all outcomes...
A critical challenge for tumour segmentation models is the ability to adapt diverse clinical settings, particularly when applied poor-quality neuroimaging data. The uncertainty surrounding this adaptation stems from lack of representative datasets, leaving top-performing without exposure common artifacts found in MRI data throughout Sub-Saharan Africa (SSA). We replicated a framework that secured 2nd position 2022 BraTS competition investigate impact dataset composition on model performance...
PHYSICIANS STILL are working out the best approach to dealing with young women infected human papillomavirus (HPV), alone or in conjunction intraepithelial neoplasia (please see accompanying article). Donald Goldstein, MD, of Boston's Children's Hospital says, "We treat [the infection site] trichloroacetic acid, we just follow patient at sixmonth intervals." Ralph M. Richart, professor pathology Columbia University College Physicians and Surgeons New York City, tells clinicians "follow that...