Medical Image Analysis

Transcription

1 Computer assisted Image Analysis VT04 29 april 2004 Medical Image Analysis Lecture 10 (part 1) Xavier Tizon Medical Image Processing Medical imaging modalities XRay,, CT Ultrasound MRI PET, SPECT Generic problems in Medical Image Processing Enhancement Registration Segmentation Interpretation Visualization of Medical Images MPR, MIP Surface and Volume rendering Images are acquired to get information about Anatomy and Physiology of a patient US MRI PET CT Use of XRays 1975 Computed Tomography

2 Xray technique Pulmonary Musculo-skeletal skeletal Angiography Angiography Mammography 2

3 CT technique CT: skeleton - neuro abdominal angiography Ultrasound Imaging 3

4 Cardiac imaging abdominal imaging Angiography Gynecology Obstetrics Positron Emission Tomography : the scanner Gynecology Obstetrics 4

5 PET: principles Positron Emission Tomography : production of radioactive products PET : examples Scintigraphy (SPECT): imaging device Nuclear Imaging Application to the detection of bone metastases 5

6 Computerised Image Analysis VT03 5/4/2004 MR tomograph T1 Musculo-skeletal (joints) T2 PDW neurological Multiple sclerosis angiography angiography 6

7 abdominal Cardiac imaging Functional imaging Other medical imaging modalities Microscopy Generic problems in Medical Image Processing Enhancement Registration Segmentation Interpretation Enhancement Noise (ex. MRI) Requires good knowledge of imaging physics And a good approximation algorithm 7

8 Background Ex: MRI Field variations produce non-uniform background Corrected by fitting a low-order order polynomial to the image Enhancement Registration Registration = matching 2 volumes by applying geometric correction to one of them The need for registration Study over time Fusion of different imaging modalities Matching to an atlas Organs movement Magnetic Resonance Imaging Computed tomography MRI gives anatomical information CT gives anatomical information Positron Emission Tomography Single Photon Emission Tomography PET gives functional information SPECT gives functional information 8

9 Reference Study Choose starting par Transform Study Evaluate similarity (cost function) Choose new set of parameters Yes Converged? No Application: surgery Segmentation & interpretation Segmentation: the need for more sophisticated algorithms Deformable models Watershed Bildanalys II Level set methods Fuzzy connectedness Interpretation Labeling from segmentation result Top-down image analysis Expert systems Artificial Intelligence Visualization of Medical Images Multi-Planar Reconstruction 2D 3D Multi-Planar Reconstruction Maximum Intensity Projection Surface Rendering Volume Rendering 9

10 Maximum Intensity Projection Shaded Surface Display (SSD) Preliminary segmentation Voxel set surface ( with for ex. marching cube) Surface elements rendered according to some illumination model Optionally texture 10

11 Volume Rendering Reflexion/transmission properties assigned to each voxel Visualization of Computed Tomography volumetric data Volume rendering Visualization of Ultrasound volumetric data Visualization of «The Visible Human» 11

12 Perspective Fusion of techniques (MR, CT, PET, ) Dual imaging devices Image Processing Interventional use of Medical Images Real-time imaging Virtual surgery Higher power BUT tougher problems Increase of computation capabilities Increase of resolution, nb of dimensions, physician s demand Complete automation is a DREAM Amount of data too important Good interaction is more reliable Visible Human Project Links Going further Links Come pay us a visit! PET/CT scan protocol Spiral CT (1-8 min total) Corrections: scatter attenuation Fused PET/CT Whole-body PET (6-40 min total) CT PET CT PET Reconstruction: FORE + OSEM CT PET 12