A5078406032- Advanced Radiotherapy Techniques
- Medical Imaging Techniques and Applications
- Radiomics and Machine Learning in Medical Imaging
- Radiation Detection and Scintillator Technologies
- Rheumatoid Arthritis Research and Therapies
- Image and Signal Denoising Methods
- Generative Adversarial Networks and Image Synthesis
- Advanced Image Processing Techniques
- AI in cancer detection
- Advanced X-ray and CT Imaging
- Radiation Therapy and Dosimetry
- IoT and Edge/Fog Computing
- Urological Disorders and Treatments
- Gamma-ray bursts and supernovae
- Advanced Malware Detection Techniques
- Chronic Myeloid Leukemia Treatments
- Inflammasome and immune disorders
- Advanced Neural Network Applications
- Thyroid Disorders and Treatments
- Hemodynamic Monitoring and Therapy
- Autoimmune and Inflammatory Disorders Research
- Particle Detector Development and Performance
- Nuclear Physics and Applications
- Lung Cancer Diagnosis and Treatment
- Spacecraft Design and Technology
Shaikh Zayed Postgraduate Medical Institute
2022-2023
Monklands Hospital
2023
Jinnah Postgraduate Medical Center
2022
Mayo Hospital
2022
IMEC
2019-2020
UCLouvain
2018-2019
Monte Carlo (MC) algorithms offer accurate modeling of dose calculation by simulating the transport and interactions many particles through patient geometry. However, given their random nature, resulting distributions have statistical uncertainty (noise), which prevents making reliable clinical decisions. This issue is partly addressable using a huge number simulated but computationally expensive as it results in significantly greater computation times. Therefore, there trade-off between...
For prostate cancer patients, large organ deformations occurring between the sessions of a fractionated radiotherapy treatment lead to uncertainties in doses delivered tumour and surrounding organs at risk. The segmentation those structures cone beam CT (CBCT) volumes acquired before every session is desired reduce uncertainties. In this work, we perform fully automatic bladder CBCT with u-net, 3D convolutional neural network (FCN). Since annotations are hard collect for volumes, consider...
Introduction Rheumatoid arthritis (RA) is a chronic autoimmune disorder with variable disease course including periods of flares and remissions. High activity in terms score-28 (DAS-28) results significant morbidity. Hypothyroidism found to be associated higher DAS-28 scores RA. This study planned determine overt subclinical hypothyroidism its correlation the score patients Methodology was conducted from June 2021 March 2022 at department rheumatology immunology Shaikh Zayed Hospital,...
Objective To identify the factors which lead to delay in diagnosis and initiation of disease-modifying anti-rheumatic drugs (DMARDs) rheumatoid arthritis (RA) patients their impact on disease outcome functional ability. Methodology This cross-sectional study was conducted from June 2021 May 2022 at Department Rheumatology Immunology, Sheikh Zayed Hospital, Lahore. Inclusion criteria were aged >18 years who diagnosed with RA, based American College (ACR) 2010. Delay defined as any sort leads...
In radiotherapy treatment planning, manual annotation of organs-at-risk and target volumes is a difficult time-consuming task, prone to intra inter-observer variabilities. Deep learning networks (DLNs) are gaining worldwide attention automate such annotative tasks because their ability capture data hierarchy. However, for better performance DLNs require large number samples whereas annotated medical scarce. To remedy this, augmentation used increase the training that enables robust by...
With the advent of Deep Learning (DL) techniques, especially Generative Adversarial Networks (GANs), data augmentation and generation are quickly evolving domains that have raised much interest recently. However, DL techniques demanding since, medical is not easily accessible, they suffer from insufficiency. To deal with this limitation, different used. Here, we propose a novel unsupervised data-driven approach for can generate 2D Computed Tomography (CT) images using simple GAN. The...
ConclusionA new method was presented that greatly improves the TG modeling.This can be easily implemented in commercial TPSs and has potential to further increase their accuracy, especially for MLCs with rounded leaf ends.This is currently patent pending status.
Recent technological developments in wireless and sensor networks have led to a paradigm shift interacting with everyday objects, which nurtured the concept of Internet Things (IoT). However, low-powered nature IoT devices generally becomes hindrance that makes them vulnerable wide array attacks. Among these, emergence rogue is quickly becoming major security concern. Rogue are malicious typically execute different kinds cyberattacks by exploiting weaknesses access control schemes...
Objective: To compare the hepatotoxicity in Leflunomide vs Methotrexate rheumatoid arthritis patients. Study design: Cross sectional study. Place and duration of study: was conducted from Jun 2021 to Mar 2022 at Department Rheumatology immunology Sheikh Zayed Hospital Lahore. Methodology: Inclusion criteria were any patient aged between 18-70 years males females. Patients who diagnosed with RA according ACR 2010. Exclusion pregnancy, Known case hepatitis B or C, patients having known...
The Gamma-ray Module (GMOD) is an experiment designed for the detection of gamma-ray bursts in low Earth orbit as principal scientific payload on a 2-U CubeSat, EIRSAT-1. GMOD comprises cerium bromide scintillator coupled to silicon photomultipliers which are processed and digitised by bespoke ASIC. Custom firmware motherboard has been designed, implemented tested MSP430 microprocessor manages including readout, storage configuration system. verified series experiments testing response over...