Medical Imaging AI Course Index — Dataplexa

Medical Imaging AI

Medical Imaging AI
Course Index

33 Lessons · 3 Levels

Complete medical imaging AI pipeline in Python — DICOM/NIfTI ingestion, CNN classifiers, U-Net segmentation, MONAI 3D models, and Grad-CAM explainability. Covers MONAI Deploy SDK, FDA 510(k), CE Mark, CDSCO India & 4 real clinical AI builds.

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33Lessons

3Levels

4Projects

FreeAccess

Level IDICOM, Imaging Modalities & CNN FoundationsLessons 1–10

Medical Imaging AI Overview

X-ray, CT, MRI & PET Modalities

DICOM Standard & pydicom

Reading DICOM with Python

NIfTI Format & 3D Volume Data

Medical Image Preprocessing

Medical Image Augmentation

CNN Architectures

Transfer Learning: ResNet & Dense

MONAI Setup & Core APIs

Level IIDeep Learning Models & TechniquesLessons 11–22

X-ray & Pathology Classes

Lesion & Nodule Detection

Semantic Segmentation with U-Net

3D Organ Segmentation with MONAI

Pathology Slide Segmentation

Image Registration & Alignment

Radiomics Feature Extraction

Grad-CAM & SHAP Explainability

Imbalanced Dataset Handling

Federated Learning

MONAI Label: AI-Assisted Annotation

Medical Imaging Foundation Models

Level IIIRegulation, Deployment & ProjectsLessons 23–33

FDA 510(k) AI Regulation

CE Mark & CDSCO Regulations

MONAI Deploy SDK

DICOM SR & Structured Reporting

OHIF Viewer & DICOMweb

AWS & GCP Health APIs

MLflow & TensorBoard

Build a Chest X-ray Classifier

Build a Tumor Segmentation Model

Build a Radiology AI Pipeline

Build a Pathology Slide Analyzer

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Medical Imaging AI Course Index

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