http://ee.sharif.edu/~miap/Files/A%20Survey%20of%20Medical%20Image%20Registration.pdf

A survey of medical image registration.

An overview is presented of the medical image processing literature on mutual-information-based registration. The aim of the survey is threefold: an introduction for those new to the field, an overview for those working in the field, and a reference for those searching for literature on a specific application. Methods are classified according to the different aspects of mutual-information-based registration. The main division is in aspects of the methodology and of the application. The part on methodology describes choices made on facets such as preprocessing of images, gray value interpolation, optimization, adaptations to the mutual information measure, and different types of geometrical transformations. The part on applications is a reference of the literature available on different modalities, on interpatient registration and on different anatomical objects. Comparison studies including mutual information are also considered. The paper starts with a description of entropy and mutual information and it closes with a discussion on past achievements and some future challenges.

/pdf/mutual-information-based-registration-of-medical-images-a-4xrv2limmo.pdf

Mutual-information-based registration of medical images: a survey

https://www-sop.inria.fr/asclepios/Publications/Tom.Vercauteren/Eval14NonlinearRegistration-Klein-NeuroImage09.pdf

Evaluation of 14 nonlinear deformation algorithms applied to human brain MRI registration.

Image registration is an important enabling technology in medical image analysis. The current emphasis is on development and validation of application-specific non-rigid techniques, but there is already a plethora of techniques and terminology in use. In this paper we discuss the current state of the art of non-rigid registration to put on-going research in context and to highlight current and future clinical applications that might benefit from this technology. The philosophy and motivation underlying non-rigid registration is discussed and a guide to common terminology is presented. The core components of registration systems are described and outstanding issues of validity and validation are confronted.

/pdf/non-rigid-image-registration-theory-and-practice-1uy6a2rpqc.pdf

Non-rigid image registration: theory and practice

Computerized Image Registration approaches can offer automatic and accurate image alignments without extensive user involvement and provide tools for visualizing combined images. The aim of this survey is to present a review of publications related to Medical Image Registration. This paper paints a comprehensive picture of image registration methods and their applications. This paper is an introduction for those new to the ﬁeld, an overview for those working in the ﬁeld and a reference for those searching for literature on a speciﬁc application. Methods are classiﬁed according to the diﬀerent aspects of Medical Image Registration.

/pdf/survey-of-medical-image-registration-2n4ysq1kfc.pdf

Survey of Medical Image Registration

ObjectiveA fully automatic multimodality image registration algorithm is presented. The method is primarily designed for 3D registration of MR and PET images of the brain. However, it has also been successfully applied to CT-PET, MR-CT, and MR-SPECT registrations.Materials and MethodsThe head contou

A fully automatic multimodality image registration algorithm.

Detection of scattered gamma quanta degrades image contrast and quantitative accuracy of single-photon emission computed tomography (SPECT) imaging. This paper reviews methods to characterize and model scatter in SPECT and correct for its image degrading effects, both for clinical and small animal SPECT. Traditionally scatter correction methods were limited in accuracy, noise properties and/or generality and were not very widely applied. For small animal SPECT, these approximate methods of correction are often sufficient since the fraction of detected scattered photons is small. This contrasts with patient imaging where better accuracy can lead to significant improvement of image quality. As a result, over the last two decades, several new and improved scatter correction methods have been developed, although often at the cost of increased complexity and computation time. In concert with (i) the increasing number of energy windows on modern SPECT systems and (ii) excellent attenuation maps provided in SPECT/CT, some of these methods give new opportunities to remove degrading effects of scatter in both standard and complex situations and therefore are a gateway to highly quantitative single- and multi-tracer molecular imaging with improved noise properties. Widespread implementation of such scatter correction methods, however, still requires significant effort.

http://www.guillemet.org/irene/article/PMBscatter2011.pdf

Review and current status of SPECT scatter correction.

There is increasing interest in being able to automatically register medical images from either the same or different modalities. Registered images are proving useful in a range of applications, not only providing more correlative information to aid in diagnosis, but also assisting with the planning and monitoring of therapy, both surgery and radiotherapy. The practising nuclear medicine specialist is faced with a dilemma in choosing an appropriate method since the literature in the field is extensive, with conflicting evidence as to what methods are optimal. Although most barriers to implementing registration in routine practice have been removed, there remains a lack of commercial, validated software. The alternative is to install a dual-modality instrument. The objective of this review is to present a general overview of medical image registration with emphasis on the application and issues relevant to nuclear medicine.

Image registration: an essential tool for nuclear medicine.

Although the potential benefits of maximum likelihood reconstruction have been recognised for many years, the technique has only recently found widespread popularity in clinical practice. Factors which have contributed to the wider acceptance include improved models for the emission process, better understanding of the properties of the algorithm and, not least, the practicality of application with the development of acceleration schemes and the improved speed of computers. The objective in this article is to present a framework for applying maximum likelihood reconstruction for a wide range of clinically based problems. The article draws particularly on the experience of the three authors in applying an acceleration scheme involving use of ordered subsets to a range of applications. The potential advantages of statistical reconstruction techniques include: (a) the ability to better model the emission and detection process, in order to make the reconstruction converge to a quantitative image, (b) the inclusion of a statistical noise model which results in better noise characteristics, and (c) the possibility to incorporate prior knowledge about the distribution being imaged. The great flexibility in adapting the reconstruction for a specific model results in these techniques having wide applicability to problems in clinical nuclear medicine.

Brian F. Hutton

Papers

A fully automatic multimodality image registration algorithm.

Review and current status of SPECT scatter correction.

Image registration: an essential tool for nuclear medicine.

A clinical perspective of accelerated statistical reconstruction

Software for image registration: algorithms, accuracy, efficacy.