Assessment of MR image deformation for stereotactic neurosurgery using a tagging sequence

A tagging sequence is used to assess MR image deformations before a stereotactic neurosurgical procedure, in a test model and in two patients. This pulse sequence superimposes narrow parallel orthogonal tag lines on an image, which can be used as an internal reference frame. Image deformation is directly related to surface area variations in the squares produced by the tagging-sequence pulses. Small spatial deformations of the tags can be detected on the images used for measuring stereotactic-target spatial coordinates. A threshold of 2 SD guarantees that the distortion is smaller than one pixel

Image quality in CT: From physical measurements to model observers

Evaluation of image quality (IQ) in Computed Tomography (CT) is important to ensure that diagnostic questions are correctly answered, whilst keeping radiation dose to the patient as low as is reasonably possible. The assessment of individual aspects of IQ is already a key component of routine quality control of medical x-ray devices. These values together with standard dose indicators can be used to give rise to 'figures of merit' (FOM) to characterise the dose efficiency of the CT scanners operating in certain modes. The demand for clinically relevant IQ characterisation has naturally increased with the development of CT technology (detectors efficiency, image reconstruction and processing), resulting in the adaptation and evolution of assessment methods. The purpose of this review is to present the spectrum of various methods that have been used to characterise image quality in CT: from objective measurements of physical parameters to clinically task-based approaches (i.e. model observer (MO) approach) including pure human observer approach. When combined together with a dose indicator, a generalised dose efficiency index can be explored in a framework of system and patient dose optimisation. We will focus on the IQ methodologies that are required for dealing with standard reconstruction, but also for iterative reconstruction algorithms. With this concept the previously used FOM will be presented with a proposal to update them in order to make them relevant and up to date with technological progress. The MO that objectively assesses IQ for clinically relevant tasks represents the most promising method in terms of radiologist sensitivity performance and therefore of most relevance in the clinical environment.publisher: Elsevier articletitle: Image quality in CT: From physical measurements to model observers journaltitle: Physica Medica articlelink: http://dx.doi.org/10.1016/j.ejmp.2015.08.007 content_type: article copyright: Copyright © 2015 Associazione Italiana di Fisica Medica. Published by Associazione Italiana di Fisica in Medicinastatus: publishe

Image quality in CT: From physical measurements to model observers

KUVAN LAATU TIETOKONETOMOGRAFIASSA: FYSIKAALISISTA MITTAUKSISTA MATEMAATTISEEN KUVA-ANALYYSIIN Tietokonetomografia (TT)-kuvantamisessa kuvan laadun arviointi on tärkeää jotta saavutetaan diagnostiikan asettamat vaatimukset ja samaan aikaan tulisi potilaan säteilyannos pitää mahdollisimman pienenä. Kuvan laatuun vaikuttavien yksittäisten tekijöiden arviointi on tärkeä osa lääketieteellisten röntgenlaitteiden laaduntarkkailua. Kyseiset laatutekijät muodostavat yhdessä tavanomaisten annosindikaattoreiden kanssa tunnusluvut (’figures of merit’, FOM), joiden avulla voidaan määritellä TT-laitteiden optimaalinen annostaso. Tietokonekuvantamisessa tapahtunut kehitys (detektoreiden tehokkuus, kuvankäsittely ja -prosessointi) ovat luonnollisesti lisänneet kliinisen kuvanlaadun vaatimuksia, jotka puolestaan ovat johtaneet arviointimenetelmien sopeuttamiseen ja kehittämiseen. Tämä kirjallisuuskatsaus esittelee erilaisia TT-kuvantamisen laadunarviointi-menetelmiä: fysikaalisiin parametreihin perustuvista mittauksista aina kliinisiin lähestymistapoihin (esim. matemaattiset kuva-analyysit) mukaan lukien ihmisen itse tekemä havainnointi. Työssä tuodaan esille lähinnä standardikuvantamiseen liittyviä kuvanlaatumenetelmiä. Työn tuloksena esitetään tunnuslukujen päivittämistä nykyteknologian vaatimusten mukaiseksi

A Technique for Simulating the Effect of Dose Reduction on Image Quality in Digital Chest Radiography

Purpose: The purpose of this study is to provide a pragmatic tool for studying the relationship between dose and image quality in clinical chest images. To achieve this, we developed a technique for simulating the effect of dose reduction on image quality of digital chest images. Materials and Methods: The technique was developed for a digital charge-coupled-device (CCD) chest unit with slot-scan acquisition. Raw pixel values were scaled to a lower dose level, and a random number representing noise to each specific pixel value was added. After adding noise, raw images were post processed in the standard way. Validation was performed by comparing pixel standard deviation, as a measure of noise, in simulated images with images acquired at actual lower doses. To achieve this, a uniform test object and an anthropomorphic phantom were used. Additionally, noise power spectra of simulated and actual images were compared. Also, detectability of simulated lesions was investigated using a model observer. Results: The mean difference in noise values between simulated and real lower-dose phantom images was smaller than 5% for relevant clinical settings. Noise power spectra appeared to be comparable on average but simulated images showed slightly higher noise levels for higher spatial frequencies and slightly lower noise levels for lower spatial frequencies. Comparable detection performance was shown in simulated and actual images with slightly worse detectability for simulated lower dose images. Conclusion: We have developed and validated a method for simulating dose reduction. Our method seems an acceptable pragmatic tool for studying the relationship between dose and image quality