Wavelets Medical Image Processing Projects
Per Henrik Hogstad -Mathematics -Statistics -Physics(Main subject: Theoretical Nuclear Physics) -Computer Science -Programming / Objectorienting -Algorithms and Datastructures -Databases -Digital Image Processing -Supervisor Master Thesis -Research -PHH:Mathem of Wavelets + Computer Application Wavelets/Medicine -Students:Application + TestWavelets/Medicine
ResearchResearch SINTEF Unimed Ultrasound in Trondheim The Norwegian Radiumhospital in Oslo Sørlandet Hospitalin Kristiansand / Arendal Mathematics - Computer Science - Medicine
Mathematics Computer Science Medicine SINTEF Unimed Ultrasound in Trondheim -Detection of blood vessel in ultra sound image The Norwegian Radiumhospital in Oslo -Linear accelerator -Computing patient position -Databases -Image processing ( Wavelets) Sørlandet Hospitalin Kristiansand -Bone thickness -Blood vessel thickness in liver Sørlandet Hospital in Arendal -IR diagnostic
Research The Norwegian Radiumhospital in Oslo -Control of the Linear Accelerator -Databases (patient/employee/activity) -Computations of patientpositions -Mathematical computations of medical image information -Different imageformat (bmp, dicom, …) -Noise Removal -Graylevel manipulation (Histogram, …) -Convolution, Gradientcomputation -Multilayer images -Transformations (Fourier, Wavelet, …) -Mammography -... Wavelet
DNR Linear Accelerator Databases Patient Position Image processing
Radiation Theraphy - Patient Position Referance pictureControl picture
Digital Image Processing Manipulation of images by computer Input ImageComputerOutput Image Digital Image Processing
Image Tranformation Original ImageTranformed Image
Histogram
Histogram Equalization
Convolution
Fourier-transformation of a square wave f(x) square wave (T=2) N=2 N=10 N=1
Image Transformation Fourier Transformation (2-dim)
Wavelets New mathematical method with many interesting applications Divide a function into parts with frequency and time/position information Signal Processing-Image Processing-Astronomy/Optics/Nuclear Physics Image/Speech recognition-Seismologi-Diff.equations/Discontinuity …
Wavelet transform has been perhaps the most exciting development in the last decade to bring together researchers in several different fields: Seismic Geology Signal processing (frequency study, compression, …) Image processing (image compression, video compression,...) Denoising data Communications Computer science Mathematics Electrical Engineering Quantum Physics Magnetic resonance Musical tones Diagnostic of cancer Economics … Interesting applications The subject of Wavelets is expanding at a tremendous rate
Introduction to Wavelets
Wavelets are building blocks that can quickly decorrelate data. At the present day it is almost impossible to give a precise definition of wavelets. The research field is growing so fast and novel contributions are made at such a rate that even if one manages to give a definition today, it might be obsolute tomorrow. One, very vague, way of thinking about wavelets could be: Wavelets = Building blocks Wavelets are building blocks for general functions.Wavelets are building blocks for general functions. Wavelets have space-frequency localization. Wavelets have space-frequency localization. Wavelets have fast transform algorithms. Wavelets have fast transform algorithms.
Wavelets are mathematical functions that can cut up data into different frequency components, and then study each component with a resolution matched to its scale. Wavelets have advantages over traditional Fourier methods in analyzing physical situation where the signal is transient or contains discontinuities and sharp spikes. Frequency / Transient signals / Discontinuity Adopting a whole new mindset or perspective in prosessing data Data
Wavelets - Different scales
CWT - Time and frequency localization Time Frequency Small a: CWT resolve events closely spaced in time. Large a: CWT resolve events closely spaced in frequency. CWT provides better frequency resolution in the lower end of the frequency spectrum. Wavelet a natural tool in the analysis of signals in which rapidly varying high-frequency components are superimposed on slowly varying low-frequency components (seismic signals, music compositions, pictures…).
Image Tranformation Details Original Image Details Image The rest of the Image
Discrete Wavelet-transformation
Compress 1:50 JPEGWavelet Original
Analysis /Synthesis Example J=5 Num of Samples: 2 J = 32
Analysis Synthesis J=5 Sampling: 2 5 = 32 j=4j=5j=3j=2j=1j=0
j=4j=5j=3j=2j=1j=0
Filtering / Compression Data compression Remove low W-values Lowpass-filtering Replace W-values by 0 for low a-values Highpass-filtering Replace W-values by 0 for high a-values
Wavelet Transform Morlet Wavelet Fourier/Wavelet Fourier Wavelet
Wavelet Transform Morlet Wavelet Fourier/Wavelet Fourier Wavelet
Wavelet Transform Morlet Wavelet - Visible Oscillation
Wavelet Transform Morlet Wavelet - Non-visible Oscillation [1/2]
Wavelet Transform Morlet Wavelet - Non-visible Oscillation [2/2]
Wavelets Basic Knowledge - Informatics - Programming / Object oriented (Java / C++) - Mathematics - Lineær algebra(Vektor Space / Basis Functions / Matrices / … ) - Fourier Analysis - Statistics - Physics
Definition of The Continuous Wavelet Transform CWT The continuous-time wavelet transform (CWT) of f(x) with respect to a wavelet (x): L 2 (R)
Wavelet Transform
Wavelet Transform Tumour
The Norwegian Radiumhospital Mammography Diameter Relative contrast Number of microcalcifications
The Norwegian Radiumhospital Mammography - Mexican Hat - 2 Dim
The Norwegian Radiumhospital Mammography
Arthritis Measure of bone Morlet External part E/I bone edge Krsand
Thickness of blood vessel in liver Morlet Krsand
ThicknessThickness Mexican Hat Krsand
Arendal Diagnostics - IR radiation
Ultrasound Image - Edge detection SINTEF – Unimed – Ultrasound - Trondheim -Ultrasound Images -Egde Detection -Noise Removal -Egde Sharpening -Edge Detection -Edge Computation
Ultrasound Image - Edge detection SINTEF – Unimed – Ultrasound - Trondheim Aorta with ProthesisUltra Sound Image
Edge Detection Convolution
Edge detection Wavelet Mexican Hat
Edge detection Scalogram
Edge detection One beam
Edge detection Scalogram
Edge Detection Wavelet - Scale Energy Wavelet Transform Inv Wavelet Transform Wavelet scale dependent spectrum Energy of the signal A measure of the distribution of energy of the signal f(x) as a function of scale.
Edge detection Wavelet - Max Energy Scale
Edge detection Wavelet - Different Edges
Methods for prepreparing of Image in front of Wavelet transform 1Noise removal Hard Soft Semi-soft 2Egde sharpening 3Different Wavelets
Noise Removal Thresholding HardSoftSemi-Soft
Noise Removal Syntetic Image 45 Wavelets test Original Original+ point spread function + white gaussian noise
Noise Removal Syntetic Image
Noise Removal Ultrasound Image Original Semi-soft Soft
Edge sharpening
Different Wavlets
Edge Computing
Mathematical Image Operation - Application
End