MR Glossary

Core concepts of magnetic resonance imaging, of fMRI and diffusion MRI analysis, and of the AI methods used in MRI, with their Turkish equivalents.

#

Turkish: Üç boyutlu görüntüleme

Imaging in which a whole volume is excited and encoded with phase encoding in two directions, instead of slice by slice. It gives thin, gap-free slices and high SNR, MPRAGE being an example.

Related: MPRAGEPhase encoding

A

Turkish: Katlanma artefaktı

Tissue outside the field of view folding onto the opposite side of the image. It usually happens along the phase-encoding direction. A larger field of view or oversampling fixes it.

Turkish: Anomali tespiti

A model trained only on normal images flagging regions that depart from that norm. It is used to find lesions when labelled patient data are scarce.

Related: Normative modellingGenerative model

Turkish: Dikkat mekanizması

A way for a network to learn which parts of the input matter most for each output and weight them accordingly. Its cost grows with the square of the input length, so it can be expensive for high-resolution images.

Related: TransformerState-space model

B

BIDS

BIDS

A set of rules for organising brain imaging data with standard file names and folders (Brain Imaging Data Structure). It makes data easier to share and to process with automated pipelines.

Related: Preprocessing

Turkish: Beyin yaşı tahmini

A model trained on MRI scans of healthy people predicting the apparent age of a new person's brain. The gap between predicted and chronological age is studied as a marker of ageing and disease.

Related: RegressionNormative modelling

C

Turkish: Kardiyak ve solunum tetikleme

Synchronising data acquisition with the heartbeat or breathing, using ECG, a pulse sensor, a respiratory belt or navigator signals. It reduces motion artifacts.

Related: Motion artifact

Turkish: Sınıf dengesizliği

One class having far fewer examples than the others, as with a rare disease. Accuracy becomes misleading, and weighting, resampling and balanced metrics are needed.

Related: ClassificationROC curve and AUC

Turkish: Küme tabanlı çıkarım

Applying a voxel threshold first and then declaring large enough clusters of adjacent voxels significant. A lenient initial threshold inflates the false-positive rate.

Related: Multiple comparisons correction

Turkish: Bobin birleştirme

Merging the images from each channel of a multichannel receiver into one image. The simplest method is the root sum of squares (RSS). Combination with coil sensitivity maps preserves phase.

Related: Receive array coilSENSE

Turkish: Kontrast-gürültü oranı

The signal difference between two tissues divided by the noise. It measures how well a structure stands out from its surroundings.

Related: Signal-to-noise ratio

Turkish: Evrişimli sinir ağı

A neural network that learns local features with small filters sliding over the image. It has long been the standard architecture for image tasks such as denoising, reconstruction and segmentation.

Related: U-NetDeep learning

Turkish: Çapraz doğrulama

Splitting data into folds and repeatedly training and testing the model, holding out a different fold each time. If model settings are also being tuned, nested cross-validation should be used.

Related: Training, validation and test setsData leakage

D

Turkish: Veri artırma

Varying training images with rotations, shifts, contrast changes and similar operations so the model learns more general features.

Related: Overfitting

Turkish: Veri tutarlılığı

A step that keeps the network's output consistent with the k-space data that were actually measured. Measured points are kept, and the network only fills in what is missing. It reduces the risk of hallucination.

Related: Physics-guided networkk-spaceHallucination

Turkish: Veri sızıntısı

Information from the test data entering the training process, for example selecting features on the whole dataset or having the same person's scans in both training and test sets. It makes performance look far better than it is.

Related: Cross-validationTraining, validation and test sets

Turkish: Derin öğrenme tabanlı geriçatım

Reconstruction that uses trained neural networks to recover images from undersampled or noisy data. Methods that build the physics model into the network tend to be more reliable. Results should be checked for structures the network may hallucinate.

Related: Image reconstructionCompressed sensing

Turkish: Gürültü giderme

Reducing random noise in an image while keeping detail. Learning-based denoising is used to make up for the SNR lost in short or high-resolution scans.

Related: Signal-to-noise ratioSuper-resolution

Turkish: Tanısal duyarlılık ve özgüllük

Sensitivity is the share of truly affected cases that are correctly detected, specificity the share of unaffected cases that are correctly ruled out. Not to be confused with magnetic susceptibility in MRI.

Related: ROC curve and AUCClassification

Turkish: Dice katsayısı

A measure of overlap between two segmentations, from 0 to 1, where 1 means perfect overlap. It is used to compare automatic segmentation with expert outlines.

Related: Segmentation

Turkish: Difüzyon verisinde gürültü giderme

Reducing noise by exploiting the shared structure across many diffusion images. Marchenko-Pastur principal component analysis (MP-PCA) is a common method and is usually the first preprocessing step.

Related: DenoisingPreprocessing

Turkish: Difüzyon tensör görüntüleme

A method that measures diffusion along many gradient directions and estimates a tensor in each voxel. Fractional anisotropy (FA) maps and white-matter tractography are derived from it.

Related: Diffusion-weighted imaging

Turkish: Difüzyon ağırlıklı görüntüleme

Imaging that is sensitive to the random motion of water molecules. Strong gradients reduce the signal of moving spins. Sensitivity is set by the b-value (s/mm²), and results are also shown as apparent diffusion coefficient (ADC) maps.

Related: Diffusion tensor imagingEcho planar imaging

Turkish: Dixon yöntemi

A method that uses the phase difference between water and fat to compute separate water and fat images from images taken at a few echo times. It gives robust fat suppression and quantifies fat fraction.

Related: Fat suppressionChemical shift

Turkish: Alan uyarlaması

Methods that adapt a model trained in one domain to another, with few examples or unlabelled data. They matter for models that must work on data from different sites.

Related: Domain shiftFine-tuning

Turkish: Dağılım kayması

The data a model meets differing from its training data, for example another scanner, field strength, sequence or patient group. Performance can drop sharply.

Related: Domain adaptationFederated learning

E

Turkish: Eko

A regrowth of decayed signal at a set time, created by restoring phase coherence. Refocusing uses a 180° RF pulse (spin echo) or a reversal of the gradient (gradient echo).

Related: Spin echoGradient echoEcho time

Turkish: EPI bozulması

Stretching or compression of EPI images caused by field inhomogeneity and the low bandwidth along the phase-encoding direction. It can be corrected with an extra scan using reversed phase encoding.

Turkish: Açıklanabilirlik

Showing which image regions or features an AI model based its decision on. It matters for trust and debugging in clinical use.

Related: Uncertainty estimation

F

Turkish: Öznitelik çıkarımı

Deriving numerical descriptors from images for a model to use. Regional volumes, cortical thickness and connectivity values are hand-crafted features. Deep networks learn features directly from data.

Related: RadiomicsClassification

Turkish: Federe öğrenme

Several institutions training a shared model without exchanging patient data. Each site updates the model on its own data, and only the updates are combined. It allows learning from more varied data while protecting privacy.

Related: Domain shiftPrivacy-preserving learning

Turkish: Görüş alanı

The physical size of the imaged region, usually in millimetres. If the object is larger than the field of view, aliasing can occur.

Related: MatrixVoxelAliasing (wrap-around)

Turkish: İnce ayar

Adapting a pretrained model to a new task or dataset with further training. Parameter-efficient methods such as LoRA train only a small set of added parameters, cutting compute and memory needs.

Related: Foundation modelDomain adaptation

Turkish: Çevirme açısı

How far an RF pulse tips the net magnetization away from B₀. A 90° pulse moves it fully into the transverse plane. Gradient echo sequences usually use smaller angles.

Related: RF pulseGradient echo

Forward model

kodlama operatörü

Turkish: İleri model

The mathematical model of the physical process from image to measured data. In MRI it consists of coil sensitivities, the Fourier transform and the sampling mask. Physics-guided networks and data consistency rely on it.

Turkish: Fourier dönüşümü

A mathematical operation that splits a signal into its frequency components. In MR the inverse Fourier transform turns k-space data into an image.

Related: k-spaceImage reconstruction

Turkish: Çerçeve yer değiştirmesi

A single-number summary of head motion between consecutive volumes, in millimetres. Volumes above a threshold can be removed from analysis (scrubbing) or flagged in the model.

Related: Motion correctionNuisance regressors

Turkish: Serbest indüksiyon sönümü

The decaying signal picked up by the receive coil right after excitation. With no refocusing it decays with T2*.

Related: EchoT2* relaxation

G

Turkish: Üretken önselli geriçatım

Guiding a generative model that has learned the image distribution, usually a diffusion model, to produce images consistent with the measured data. It adapts flexibly to acquisition settings, but can be slow and needs care against hallucination.

Related: Diffusion modelData consistencyHallucination

Turkish: Gibbs halkalanması

Fine parallel lines next to sharp signal edges. They come from truncating k-space. A larger matrix or filtering reduces them.

Related: k-spaceMatrix

GRAPPA

GRAPPA

A parallel imaging method that fills missing k-space lines from neighbouring lines, using weights learned from a fully sampled calibration region.

Related: Parallel imagingSENSEk-space

Turkish: Jiromanyetik oran

The constant linking a nucleus's resonance frequency to field strength. For hydrogen, γ/2π is about 42.58 MHz/T. Each nucleus has its own value, so the scanner is tuned to a specific nucleus.

Related: Larmor frequency

H

Turkish: Harmonizasyon

Reducing systematic differences between data from different scanners and sites while keeping biological differences. Statistical methods such as ComBat or deep learning image translation are used.

Related: Domain shiftRadiomicsFederated learning

Turkish: Yüksek geçiren filtre

Removing slow drifts in the fMRI time series caused by scanner heating and physiology. The cutoff is chosen so it does not remove the slowest change in the experimental design.

Related: General linear modelNuisance regressors

I

Turkish: Görüntü çakıştırma

Estimating the transform that brings two images into spatial alignment. It can be rigid (6 degrees of freedom), affine (12) or nonlinear. Aligning a functional image to the same person's anatomical image is called coregistration.

Turkish: Görüntü sentezi

Producing an image of a contrast or modality that was not acquired, from the images that were. For example, FLAIR can be synthesised from T1- and T2-weighted images, or a CT-like image from MRI. It can shorten exams, but results must be validated before diagnostic use.

Turkish: Görüntüden görüntüye çeviri

A learning task that maps an image to another domain. It can be trained with paired data (two contrasts from the same person) or unpaired data. Image synthesis and denoising are examples.

Related: Image synthesisDenoising

Turkish: Bağımsız bileşen analizi

A method that splits data into statistically independent spatial or temporal components. In fMRI it is used to find resting-state networks and to identify components caused by motion or physiological noise.

Related: Resting-state fMRINuisance regressors

Turkish: Ters problem

The problem of recovering the unknown object that produced the measured data. MR reconstruction is an inverse problem that recovers an image from incomplete, noisy k-space data and usually has no unique solution without prior information.

Related: Forward modelRegularisationImage reconstruction

K

L

Larmor frequency

ω₀ = γB₀

Turkish: Larmor frekansı

The frequency at which spins precess around the magnetic field. It is proportional to field strength. For hydrogen it is about 64 MHz at 1.5 T and about 128 MHz at 3 T.

Related: PrecessionGyromagnetic ratioRF pulse

Turkish: Sıvı helyum

The coolant that keeps superconducting windings at operating temperature. It boils at about 4.2 K. Closed cooling systems keep losses to a minimum.

Related: Superconducting magnetQuench

M

Turkish: Manyetik parçacık görüntüleme

A modality distinct from MRI that directly measures the magnetic response of superparamagnetic iron oxide nanoparticles. A field-free point or line is scanned to map where they are and how concentrated. There is no tissue background.

Related: Gradient

Turkish: Manyetik rezonans

Nuclei placed in a strong magnetic field absorb and re-emit radio waves at their resonance frequency. MR imaging measures this signal, mostly from hydrogen nuclei in the water and fat of tissue.

Turkish: Manyetizasyon transferi

The transfer of saturation from protons bound to large molecules to the free water signal. It gives contrast sensitive to macromolecular content such as myelin.

Related: T1 relaxation

Turkish: Matris

The number of pixels in each direction of the image, for example 256 × 256. A larger matrix at the same field of view gives finer detail but lowers SNR and can lengthen the scan.

Related: Field of viewVoxelSignal-to-noise ratio

Turkish: Hareket artefaktı

Blurring and ghosting from patient motion, breathing, heartbeat or blood flow during the scan. Ghosts usually appear along the phase-encoding direction.

Related: Motion correctionPhase encoding

MPRAGE

MPRAGE

Magnetization-prepared rapid gradient echo: a high-resolution 3D T1-weighted sequence prepared with an inversion pulse. It is the usual anatomical reference scan in brain research.

Related: T1-weighted imageGradient echoInversion recovery

Turkish: MR spektroskopi

A method that measures the spectrum of chemical compounds in a volume instead of an image. In the brain, metabolites such as NAA, choline, creatine and lactate are told apart by their chemical shifts.

Related: Chemical shiftShimming

Turkish: Çok kipli öğrenme

Learning that combines different MR contrasts, other imaging modalities, clinical data or text. The sources complement each other. Coping with missing modalities is an active research topic.

Related: Image synthesisVision-language model

Turkish: Çoklu karşılaştırma düzeltmesi

Adjusting the threshold to limit chance findings when tens of thousands of voxels are tested separately. Either the family-wise error rate (FWE) or the false discovery rate (FDR) is controlled. Cluster-based and permutation tests are also common.

N

Turkish: Net manyetizasyon

The summed magnetic moment of all spins in a volume. At equilibrium it points along B₀. The measured MR signal arises when this vector is tipped into the transverse plane.

Related: RF pulseFlip angleT1 relaxation

NODDI

NODDI

Neurite orientation dispersion and density imaging: a biophysical model that estimates more tissue-specific measures, such as neurite density and orientation dispersion, from multi-shell data.

Related: Multi-shell diffusionFractional anisotropy

Turkish: Normatif modelleme

Learning the normal distribution of a brain measure by age and sex from a large healthy sample, then measuring how far individuals deviate from it. It lets patients be studied as individuals rather than as group averages.

Related: Brain age predictionAnomaly detection

O

P

Turkish: Paralel görüntüleme

An acceleration method that skips part of k-space by using the different spatial sensitivities of multichannel receive coils. The speed-up is given as the factor R.

Related: SENSEGRAPPAReceive array coil

Turkish: Kısmi Fourier

An acceleration method that uses k-space symmetry to measure only a little over half of it. Scan time drops, with a small loss of SNR.

Related: k-space

Turkish: Periferik sinir uyarımı

Tingling or muscle twitching caused by currents that rapid gradient switching induces in tissue. The scanner keeps gradient switching below this threshold.

Related: Gradient coil

Turkish: Fizik güdümlü ağ

A deep learning method that builds the MR measurement model, the encoding and coil sensitivities, into the network. The steps of an iterative reconstruction algorithm are unrolled into network layers. It is more reliable and generalises better than purely data-driven networks.

Related: Deep learning reconstructionData consistency

Turkish: Presesyon

The rotation of a spin's axis around the field direction, like the axis of a spinning top. Its rate is the Larmor frequency.

Related: Larmor frequencySpin

Turkish: Mahremiyet koruyan öğrenme

Methods that make it hard to recover personal data from a model or from shared information, during or after training. Federated learning, differential privacy and de-identification are among them.

Related: Federated learning

Turkish: Fırlatma etkisi

Ferromagnetic objects being pulled into the magnet with great force. Scissors, oxygen cylinders or chairs can cause fatal injury. Because the magnet is always on, the risk exists outside scans too.

Turkish: Proton yoğunluğu

The amount of signal-producing hydrogen nuclei in a tissue. Proton density weighted images use a long TR and short TE to reduce T1 and T2 effects and bring out this difference.

Related: Repetition timeEcho time

PSNR and SSIM

PSNR, SSIM

Turkish: PSNR ve SSIM

Two common metrics for how closely a generated image matches a reference. PSNR looks at pixel differences, SSIM at structural similarity. High values do not always guarantee diagnostic value.

Related: DenoisingImage synthesis

Turkish: Açık veri setleri

Openly shared image collections that let methods be compared. For example, fastMRI offers raw k-space data, IXI multi-contrast brain images and BraTS tumour segmentation data. Their terms of use and ethics approvals must be respected.

Related: Training, validation and test setsSegmentation

Q

Turkish: Söndürme

The rapid loss of superconductivity in the magnet. The helium boils off and is vented through the quench pipe. It can be triggered on purpose to shut down the field in an emergency. Gas leaking into the room creates a risk of asphyxiation.

R

Turkish: Radyomik

Extracting many texture, shape and intensity features from medical images and using them for diagnosis or outcome prediction. Because features depend on scanner and sequence settings, harmonisation and external validation are needed.

Related: Feature extractionHarmonisation

Turkish: Regresyon

Predicting a continuous value from images, such as age, a cognitive score or disease severity. Performance is measured with mean absolute error or correlation.

Related: Brain age predictionCross-validation

Turkish: Düzenlileştirme

A prior added to an inverse problem to pick a plausible solution among the many that fit the measurements. Total variation and wavelet sparsity are classic examples. In deep learning the prior is learned from data.

Turkish: Tekrarlama zamanı

The time between successive excitation pulses. A short TR emphasises T1 differences. Scan time is close to TR times the number of phase-encoding steps.

Related: Echo timeT1-weighted image

Turkish: Retinotopik haritalama

Mapping with fMRI how positions in the visual field are laid out across visual cortex. Rotating wedge and expanding ring stimuli or population receptive field (pRF) models are used.

Related: Functional MRIEncoding model

Turkish: RF yanığı

A burn caused by RF energy concentrating at skin contact points, cables or conductive loops formed by the body. Keeping arms and legs from touching, keeping cables off the skin and using proper pads reduce the risk.

Turkish: RF manyetik alanı

The weak magnetic field produced during an RF pulse, perpendicular to B₀ and rotating at the Larmor frequency. At high field it may not spread evenly through the body.

Related: RF pulseParallel transmission

Turkish: RF darbesi

A short burst of radiofrequency energy at the Larmor frequency. It tips the net magnetization away from equilibrium to create signal. Different pulses are used for excitation, refocusing and inversion.

RF shield

Faraday kafesi

Turkish: RF kafesi

A conductive enclosure around the magnet room that keeps outside radio signals from entering the image. If the door is not fully closed, interference lines can appear.

Related: Zipper artifact

S

Turkish: Bölütleme

Assigning every voxel to a structure or tissue, for example outlining brain tissues, a tumour or the hippocampus. It is a basic step for volume measurement and treatment planning.

Related: U-NetDice coefficient

Turkish: Öz-gözetimli öğrenme

An approach that derives a training signal from the structure of the data itself, with no labels or references. For example, measured k-space is split in two and the model learns to predict one part from the other. It is valuable when fully sampled data do not exist.

Related: Supervised learningDeep learning reconstruction

SENSE

SENSE

Sensitivity encoding: a parallel imaging method that unfolds aliased images in image space using coil sensitivity maps.

Related: Parallel imagingGRAPPA

Turkish: Eşzamanlı çok kesitli görüntüleme

Exciting several slices at once and separating them with receive coil sensitivities. In fMRI and diffusion imaging it gives whole-brain coverage at short TR.

Related: Parallel imagingEcho planar imaging

Turkish: Kesit seçimi

Applying a gradient during the RF pulse so that only spins in one slice are excited. Slice thickness is set by the pulse bandwidth and the gradient strength.

Related: GradientSlice thickness

Turkish: Kesit kalınlığı

The thickness of the excited slice in 2D imaging. Thin slices reduce partial volume effects but lower SNR.

Related: Slice selectionVoxel

Turkish: Uzamsal normalizasyon

Transforming different people's brain images into a common template space, such as MNI space. It is a prerequisite for group analysis.

Related: Motion correctionMPRAGE

Turkish: Uzamsal yumuşatma

Blurring the image with a Gaussian kernel. The kernel width is given as full width at half maximum (FWHM), often 4–8 mm. It raises SNR and evens out anatomical differences across subjects, at the cost of spatial detail.

Turkish: Özgül soğurma oranı

The rate at which the body absorbs RF energy, in W/kg. The scanner monitors SAR continuously to limit tissue heating. In normal operating mode the whole-body limit is 2 W/kg.

The quantum-mechanical angular momentum of a nucleus. Because of its spin, the hydrogen nucleus (a proton) behaves like a tiny magnet and interacts with an external magnetic field.

Related: Net magnetizationPrecession

Turkish: Spin eko

A sequence that forms an echo with a 180° refocusing pulse after a 90° excitation. It undoes field inhomogeneity effects, so it gives T2 contrast and is more robust to distortion from metal and air.

Related: EchoTurbo or fast spin echoGradient echo

Turkish: Durum uzayı modeli

A network type that processes long sequences with compute that grows linearly with input length. Selective state-space models such as Mamba offer transformer-like long-range context at lower cost and are now used in medical image synthesis and reconstruction.

Related: TransformerAttention mechanism

Turkish: Süper çözünürlük

Estimating a higher-resolution image from a lower-resolution one. It is used to obtain thin-slice images from thick-slice scans. Whether the estimated detail is real must be assessed carefully.

Related: DenoisingHallucinationVoxel

T

Turkish: T1 gevşemesi

The recovery of longitudinal magnetization after excitation (spin-lattice relaxation). T1 is the time for about 63 percent of that recovery. Fat has a short T1, cerebrospinal fluid a long one.

Turkish: T2 gevşemesi

The decay of transverse magnetization as spins lose phase coherence through spin-spin interactions. T2 is the time for the signal to fall to about 37 percent, and in tissue it is always shorter than T1.

The SI unit of magnetic flux density. Clinical and research scanners mostly run between 1.5 T and 7 T. For comparison, the Earth's field is about 50 microtesla.

Related: Main magnetic fieldFringe field

Turkish: Test zamanı uyarlaması

Briefly updating a trained model at inference time using only the incoming data itself. In reconstruction, aiming for consistency with the measured k-space can reduce the impact of domain shift.

Related: Domain shiftData consistencyDomain adaptation

Turkish: Uçuş zamanı anjiyografisi

A contrast-free vascular imaging method that relies on fresh, unsaturated blood flowing into the slice and appearing bright.

Related: Gradient echo

Turkish: Eğitim, doğrulama ve test kümeleri

Splitting data into three parts: to train the model, to choose its settings and to measure its final performance. If the same person's data appear in more than one set, performance looks better than it is.

Related: OverfittingDomain shift

Turkish: Dönüştürücü

A network architecture that models relations between parts of the input with an attention mechanism. It can capture context between distant regions. For images it works on small patches (vision transformer, ViT).

Related: Attention mechanismState-space modelFoundation model

Turkish: Hızlı spin eko

A spin echo variant that collects several echoes after one excitation using a train of refocusing pulses. It speeds up the scan by the echo train length and is the standard way to acquire T2-weighted images.

Related: Spin echoT2-weighted image

U

U-Net

U-Net

A convolutional network that first downsamples the image to gather context, then upsamples to recover detail, with skip connections between the two paths. It was designed for medical image segmentation and also serves as the backbone of many reconstruction and diffusion models.

Turkish: Belirsizlik kestirimi

Measuring how far a model's output can be trusted, at voxel or image level. It shows readers which regions deserve a careful look.

Related: HallucinationExplainability

Turkish: Eksik örnekleme

Measuring only part of k-space to speed up a scan. The speed-up is given as the factor R. The sampling mask that decides which points are measured directly affects reconstruction quality and can itself be learned.

Related: k-spaceParallel imagingCompressed sensing

V

Turkish: Görme-dil modeli

A model that processes images and text together. It can be used to match radiology reports with images, answer questions about an image or draft a report.

Related: Foundation model

Z

Turkish: Fermuar artefaktı

A zipper-like line running across the image. It usually comes from outside RF interference, for example a door left open or an electronic device brought into the room.

Related: RF shield

This page is for general information. The rules for anyone scanning at UMRAM are on the MR Safety and User Training page.