Masdar interests include software design and development, artificial intelligence, machine learning, computer vision, and medical image processing.
My interdisciplinary research ranges from investigating Physics-based Machine Learning, developing software and hardware configurated for real-time data processing, developing Deep Learning model to detect anomaly to medical imaging, developing, and designing high efficiency Deep Learning model and methods.
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Below are some of my skill areas, and I'm always eager to learn more.
Development of image processing and deep learning methods based on physics concepts
Application and development of image processing for various purposes
Medical image processing for X-ray, CT-Scan, and MRI with deep learning
Computationally applied physics concepts to solve various problems
Machine Learning, Computer Vision
Hyperspectral Imaging, Ganoderma
Large Language Model, Clustering
Embedded Deep Learning Algorithm
Radiography, Deep Learning
Blood Cell Detection, YoLo v7
Deep Learning, Medical Imaging
GANs, MRI, T1
MRI, Noise, GANs
SR-GANs, MRI
YoLo v7, MRI, Tumor
DC-GANs, Augmentation
Machine Learning, Data Acquisition
Computer Vision, deep learning
Software, Deep Learning
Arduino, Physics
Astrophotography, Fajr
Image Processing
Cryptography, Physics
Radiotherapy, Deep Learning
Microcontroler, Sensor
Research Presentations, Conferences, Public Talks
There are many different image processing methods that can be used, and the best approach for each image will vary depending on the content and quality of the original image.
I am talking about the image segmentation method on head MRI images for low-glioma segmentation. This method is very effective and has helped me a lot in my research.
Deep learning can be used to diagnose diseases, predict patient outcomes, and provide personalized treatment plans.
Development 3D MRI Segmentation Methods based on Deep Learning.
