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EEE 475

Medical Image Reconstruction and Processing

Medical imaging modalities like MRI, CT, and MPI don't hand you a picture, they hand you samples in Fourier or projection space, and turning that raw data into a diagnostically useful image is what this course is fundamentally about. You'll work through how sampling patterns (Cartesian, non-Cartesian, undersampled) dictate reconstruction strategy, implementing gridding, parallel imaging algorithms like SENSE and GRAPPA, and compressed sensing recovery across five homeworks and a project, then move into post-processing topics like denoising, registration, and segmentation. It builds directly on signals-and-systems and Fourier intuition from earlier EEE courses, and is the natural follow-on if you want to work in medical imaging research, industry MRI/CT vendors, or anywhere inverse problems show up.

Kredi3ECTS5FakülteFaculty of EngineeringBölümElectrical and Electronics EngineeringÖn koşulEEE 321KoordinatörEmine 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 475 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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