Role of AI in Radiological Image Analysis

AI, mainly deep learning with CNNs, learns patterns from large sets of labelled images to support radiologists.

Task	Example
Detection	Lung nodules on chest CT, fractures on X-ray, breast lesions on mammograms
Classification	Benign vs malignant, pneumonia vs normal
Segmentation	Tumour or organ outlines for radiotherapy planning
Image enhancement	Noise reduction, dose reduction, faster MRI reconstruction
Workflow	Triage of urgent cases (stroke, haemorrhage), auto-reporting
Quantification	Tumour volume, bone density, cardiac measurements
Prediction	Prognosis and treatment response

Benefits

Faster reading, fewer missed findings, consistency, reduced workload.

Challenges

Need for large annotated data, bias, explainability (black box), validation and regulatory approval, privacy, integration with PACS.

AI is an assistant; the radiologist remains responsible for the final diagnosis.

Exam tip

Draw the pipeline and give 4 tasks with examples.