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EEE 575

Medical Image Reconstruction and Processing

EEE 575 treats medical imaging as an inverse problem: you're handed incomplete, noisy measurements from MRI, CT, or MPI scanners and have to recover a faithful image, which means thinking carefully about sampling, Fourier-domain encoding, and the priors that make reconstruction well-posed. Expect five homeworks and a project where you actually implement the core machinery, gridding/NUFFT for non-Cartesian data, SENSE/GRAPPA for parallel imaging, compressed sensing recovery, and registration/segmentation on the post-processing side. It's a graduate elective that assumes you're comfortable with signals, linear algebra, and a bit of optimization, and it's the natural bridge from classical DSP into the reconstruction pipelines used in clinical scanners and modern imaging research.

Kredi3ECTS5FakülteFaculty of EngineeringBölümElectrical and Electronics EngineeringKoordinatörEmine Ülkü Sarıtaş

→ STARS müfredatı (resmi syllabus)

Haftalık müfredat 14 hafta

Hafta 114–20 Eyl

Giriş ve çok boyutlu Fourier transform

Introduction, Multi-dimensional Fourier Transform

Fourier transformçok boyutlu dönüşüm

Hafta 221–27 Eyl

Görüntülemeye genel bakış: MRI, CT, MPI

Imaging overview: MRI, CT, MPI

MRICTMPI

Hafta 328 Eyl – 4 Eki

Cartesian sampling ve reconstruction

Cartesian Sampling and Reconstruction, Data sampling and reconstruction in 1D, Data sampling and reconstruction in 2D/3D

Cartesian samplingreconstruction1D2D/3D

Hafta 45–11 Eki

Projection ve partial Fourier reconstruction

Image and Frequency Domain Reconstruction: Projection reconstruction (CT, MPI), Partial Fourier reconstruction in MRI

projection reconstructionpartial FourierCTMPI

Hafta 512–18 Eki

Non-Cartesian reconstruction: gridding ve NUFFT

Image and Frequency Domain Reconstruction: Non-Cartesian reconstructions: gridding, NUFFT, Examples from MRI, MPI and CT

griddingNUFFTMRIMPI

Hafta 619–25 Eki

Görüntü kalitesini artırma: denoising ve deconvolution

Improving Image Quality: Image denoising, Image deconvolution

image denoisingimage deconvolutionimage quality

Hafta 726 Eki – 1 Kas

Görüntü kalitesi: MRI off-resonance düzeltmesi

Improving Image Quality: Off-resonance correction in MRI, Correction of timing errors

off-resonance correctionMRItiming errors

Hafta 82–8 Kas

Parallel imaging ve MRI'da phased-array

Parallel Imaging: Encoding in Image and Frequency Domains, Phased-arrays in MRI

parallel imagingimage domainfrequency domainphased-array

Hafta 99–15 Kas

SENSE, GRAPPA ve coil compression

Parallel Imaging: SENSE and GRAPPA algorithms, Coil compression

SENSEGRAPPAcoil compressionparallel imaging

Hafta 1016–22 Kas

Compressed sensing: random undersampling

compressed sensingrandom undersampling

Hafta 1123–29 Kas

Compressed sensing: sparsity ve nonlinear recovery

Compressed Sensing: Sparsity/compressibility and nonlinear recovery, Model-based reconstructions

sparsitycompressibilitynonlinear recoverymodel-based reconstruction

Hafta 1230 Kas – 6 Ara

Rigid, non-rigid ve surface-based registration

Medical Image Registration: Rigid and non-rigid registration, Surface-based registration

rigid registrationnon-rigid registrationsurface-based registration

Hafta 137–13 Ara

Multi-modal registration ve image fusion

Medical Image Registration: Multi-modal registration and image fusion

medical image registrationmulti-modal registrationimage fusion

Hafta 1414–20 Ara

Tıbbi görüntülerde segmentation yöntemleri

Medical Image Segmentation: Edge-based and region-based segmentation, Atlas-based segmentation, Computer-aided diagnosis

edge-based segmentationregion-based segmentationatlas-based segmentationcomputer-aided diagnosis

Değerlendirme 100% · 4 adım

40%

10%

Homework Bi-weekly homeworks 40%

Quiz Quiz related to homeworks 40%

Project Term project 10%

Presentations Project Presentation and Interview 10%

en büyük tek kalem %40 · sınav ağırlığı %40 nasıl hesaplanıyor

Önerilen kaynaklar 2 kitap

📖

Önerilen

Handbook of MRI Pulse Sequences

Matt Bernstein, Kevin King

Xiaohong Zhou · 1st edition

📖

Önerilen

Medical Image Analysis

Atam P. Dhawan

2nd Edition · John Wiley & Sons

Bu dersi alınca · 8 öğrenme çıktısı

Develop an understanding of the fundamental applications of medical image reconstruction and processing.Bi-weekly homeworks, Term project, Project Presentation and Interview
Analyze the effects of uniform/non-uniform sampling/undersampling on the image.Bi-weekly homeworks, Term project
Reconstruct images from non-uniformly sampled data, projection data, regularly/randomly undersampled data.Bi-weekly homeworks, Term project
Implement parallel imaging and compressing sensing reconstructions for medical imaging.Bi-weekly homeworks, Term project
Apply techniques to improve image quality.Bi-weekly homeworks, Term project
Demonstrate post-processing of images for image registration and computer-aided diagnosis.Bi-weekly homeworks, Term project
Acquire an ability to learn new medical image reconstruction or processing techniques.Bi-weekly homeworks, Term project
Demonstrate sufficient knowledge to develop an advanced medical image reconstruction or processing technique.Term project, Project Presentation and Interview

Bilkent'in resmî syllabus'ünden. Sağdaki etiket o çıktının hangi değerlendirmeyle ölçüldüğünü söylüyor.

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EEE 575 için defter ekibi henüz not yazmadı.

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⚠️ FZ engelleyen şartlar

All homework assignments should be completed and submitted. Grades, except for the final project, should justify a letter grade of D or better.

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