Assessfy Pvt. Ltd Moderate 7 milestones 60 marks

Lung Cancer Image Segmentation using Various Image Processing Techniques

Real-world project · AICTE-aligned · AI-graded · Audit-ready certificate

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About this project

Lung Cancer Image Segmentation using Various Image Processing Techniques

Milestones
1.
2. Data collection (CT scan images, possibly from Kaggle or open medical datasets)
10 marks 30d
3. Data collection (CT scan images, possibly from Kaggle or open medical datasets)
10 marks 30d
4. Preprocessing (denoising, contrast enhancement)
10 marks 30d
5. Implementing segmentation algorithms (e.g., edge detection, watershed, thresholding)
10 marks 30d
6. Evaluation against annotated ground truth
10 marks 30d
7. Visualization and reporting
10 marks 30d
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Skills you'll learn
Image Processing (thresholdingfilteringsegmentation) Machine Learning basics (if extended to ML-based segmentation) Python Programming Knowledge of medical imaging standards (DICOM) Data Annotation & Preprocessing
Tools used
Python with OpenCVscikit-imageNumPyMatplotlib MATLAB (for academic use) DICOM viewers (3D SlicerRadiAnt) Jupyter Notebook
Prerequisites
Understanding of digital image processing Basic knowledge of anatomy (lungstumors) Programming skills in Python or MATLAB
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