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I will perform medical image segmentation and develop ai models
M Zeeshan
About this gig
I provide advanced AI solutions for medical imaging, specializing in 3D segmentation and neuro-oncology applications. With expertise in deep learning and Topological Data Analysis (TDA), I develop high-performance models such as U-Net, Swin UNETR, and attention-based architectures for accurate tumor, organ, and tissue segmentation.
I work with MRI/CT data (NIfTI, DICOM) and offer complete preprocessing pipelines including skull stripping, normalization, and bias correction. I also extract advanced features like Betti numbers and persistent homology to capture complex tumor structures beyond traditional CNNs.
My services include brain tumor segmentation (BraTS WT, TC, ET), radiomics feature extraction, 3D point cloud generation, and full research support with detailed technical documentation.
Whether you're a researcher, student, or startup, I deliver reliable, research-ready AI solutions tailored to your dataset.
Contact me before ordering to discuss your project.
Get to know M Zeeshan
M Zeeshan
Medical AI Researcher
- FromPakistan
- Member sinceApr 2026
Languages
English, Urdu
I am a Medical AI Researcher specializing in Deep Learning and Neuro-oncology. Currently focusing on Brain Tumor Segmentation (BraTS), 3D Point Clouds, and Topological Data Analysis (TDA), I bridge the gap between high-end research and functional implementation.
With a background in AI and Journalism, I offer a unique edge: I build complex architectures like U-Net while providing elite technical documentation. Whether you need MRI preprocessing (NIfTI/DICOM) or TDA-based feature extraction, I deliver research-grade results tailored for global MedTech startups.
My Portfolio
FAQ
What data formats do you work with?
I primarily work with NIfTI (.nii, .nii.gz) and DICOM formats. I can also process 3D point clouds and standard image formats for medical analysis.
Do you provide the source code?
Yes, all packages include the full source code (Python/PyTorch or Julia) and documentation for the developed pipeline.
What is Topological Data Analysis (TDA) in this context?
TDA is a mathematical approach I use to extract structural features like Betti numbers and persistent homology. This helps identify complex tumor shapes that traditional CNNs might overlook.
