Medical Imaging

Seeing inside the body. The Fourier foundations of imaging, X-ray and CT with radiation safety, MRI, ultrasound and nuclear medicine — how each modality forms an image and what it reveals.

• DFT & FFT — The discrete Fourier transform computes the spectrum of sampled data, and the FFT computes it fast. Learn the DFT definition, frequency bins and resolution, the radix-2 FFT and its N log N cost, windowing and spectral leakage, zero padding, amplitude scaling, real-signal FFTs, and applications — with a Python spectrum analyser.
• Medical Imaging I: X-ray, CT & Radiation Safety — Seeing inside with ionising radiation. Learn X-ray production (tube, bremsstrahlung, kVp and mAs), interactions (photoelectric, Compton), Beer–Lambert attenuation and contrast, detectors, radiography and fluoroscopy, computed tomography (projections, sinograms, filtered back-projection, Hounsfield units, helical and dual-energy CT), image quality (contrast, noise, resolution) and radiation dose and protection — with Python for attenuation, HU and dose comparisons.
• Medical Imaging II: MRI, Ultrasound & Nuclear Medicine — Imaging without X-rays — and imaging function. Learn MRI physics (spin, Larmor frequency, RF excitation, T1/T2 relaxation, gradients and k-space, contrast weighting, safety), ultrasound (acoustic impedance, reflection, attenuation, transducers, resolution, B-mode, Doppler), nuclear medicine (radiotracers, gamma cameras, SPECT, PET), and image processing basics — with Python for Larmor frequencies, T1-weighted contrast and ultrasound resolution.