Four case studies spanning X-ray classification, CT segmentation, DICOM review workflow design, and volumetric lesion analysis — presented as imaging-focused technical work rather than formal engagements.
Machine learning pipeline for analyzing X-ray images and highlighting patterns associated with common abnormalities.
Developed a Python-based medical imaging project to analyze and classify X-ray images for common abnormalities, with a focus on fractures and lung-related findings. The project included image preprocessing, feature extraction, model training, and output visualization designed to make predictions more interpretable and easier to review.
3D segmentation and reconstruction workflow for converting CT imaging data into interpretable anatomical models.
Built a 3D medical imaging case study in 3D Slicer focused on segmenting CT-based anatomical structures and generating 3D reconstructions for improved visualization. The workflow involved importing DICOM scans, isolating regions of interest, refining segmentation masks, and producing 3D renderings that make anatomical relationships easier to understand for education and imaging review.
Structured DICOM review process for navigating studies across axial, sagittal, and coronal views.
Created a structured imaging review workflow in OsiriX for navigating DICOM studies across multiple planes, organizing image series, and identifying clinically relevant visual patterns. The project emphasized efficient study review, image annotation, and consistent inspection across axial, sagittal, and coronal views to strengthen radiologic interpretation and workflow familiarity.
Case-study workflow for segmenting lesions and generating reproducible 2D and 3D measurement outputs.
Developed a lesion-focused imaging case study in 3D Slicer involving segmentation of a selected region of interest, volumetric measurement, and comparison between slice-based and 3D views. The project was designed to explore reproducible measurement practices and demonstrate how structured visualization can support more consistent review of lesion shape, location, and size.
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