Reconstructing images from their noisy and incomplete measurements is always a challenge especially for medical MR image with important details and features. This work proposes a novel dictionary learning model that integrates two sparse regularization methods: the total generalized variation (TGV) approach and adaptive dictionary learning (DL). In the proposed method, the TGV selectively regularizes different image regions at different levels to avoid oil painting artifacts largely. At the same time, the dictionary learning adaptively represents the image features sparsely and effectively recovers details of images. The proposed model is solved by variable splitting technique and the alternating direction method of multiplier. Extensive simulation experimental results demonstrate that the proposed method consistently recovers MR images efficiently and outperforms the current state-of-the-art approaches in terms of higher PSNR and lower HFEN values.

Hongyang Lu

Jingbo Wei

Qiegen Liu

Yuhao Wang

Xiaohua Deng

A Dictionary Learning Method with Total Generalized Variation for MRI Reconstruction

<i>Aim</i>. It can help improve the hospital throughput to accelerate magnetic resonance imaging (MRI) scanning. Patients will benefit from less waiting time.<i> Task</i>. In the last decade, various rapid MRI techniques on the basis of compressed sensing (CS) were proposed. However, both computation time and reconstruction quality of traditional CS-MRI did not meet the requirement of clinical use.<i> Method</i>. In this study, a novel method was proposed with the name of exponential wavelet iterative shrinkage-thresholding algorithm with random shift (abbreviated as EWISTARS). It is composed of three successful components: (i) exponential wavelet transform, (ii) iterative shrinkage-thresholding algorithm, and (iii) random shift.<i> Results</i>. Experimental results validated that, compared to state-of-the-art approaches, EWISTARS obtained the least mean absolute error, the least mean-squared error, and the highest peak signal-to-noise ratio.<i> Conclusion</i>. EWISTARS is superior to state-of-the-art approaches.

Yudong Zhang

Jiquan Yang

Jianfei Yang

Aijun Liu

Ping Sun

A Novel Compressed Sensing Method for Magnetic Resonance Imaging: Exponential Wavelet Iterative Shrinkage-Thresholding Algorithm with Random Shift

For augmented fluoroscopy during cardiac ablation, a preoperatively acquired 3D model of a patient’s left atrium (LA) can be registered to X-ray images recorded during a contrast agent (CA) injection. An automatic registration method that works also for small amounts of CA is desired. We propose two similarity measures: The first focuses on edges of the patient anatomy. The second computes a contrast agent distribution estimate (CADE) inside the 3D model and rates its consistency with the CA as seen in biplane fluoroscopic images. Moreover, temporal filtering on the obtained registration results of a sequence is applied using a Markov chain framework. Evaluation was performed on 11 well-contrasted clinical angiographic sequences and 10 additional sequences with less CA. For well-contrasted sequences, the error for all 73 frames was 7.9 <svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" style="vertical-align:-0.3499303pt" id="M1" height="7.35473pt" version="1.1" viewBox="-0.0498162 -7.0048 7.75925 7.35473" width="7.75925pt"><g transform="matrix(.013,0,0,-0.013,0,0)"><path id="g117-37" d="M535 290V340H323V533H265V340H52V290H265V84H323V290H535ZM535 -22V28H52V-22H535Z"/></g></svg> 6.3 mm and it dropped to 4.6 <svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" style="vertical-align:-0.3499303pt" id="M2" height="7.35473pt" version="1.1" viewBox="-0.0498162 -7.0048 7.75925 7.35473" width="7.75925pt"><g transform="matrix(.013,0,0,-0.013,0,0)"><use xlink:href="#g117-37"/></g></svg> 4.0 mm when registering to an automatically selected, well enhanced frame in each sequence. Temporal filtering reduced the error for all frames from 7.9 <svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" style="vertical-align:-0.3499303pt" id="M3" height="7.35473pt" version="1.1" viewBox="-0.0498162 -7.0048 7.75925 7.35473" width="7.75925pt"><g transform="matrix(.013,0,0,-0.013,0,0)"><use xlink:href="#g117-37"/></g></svg> 6.3 mm to 5.7 <svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" style="vertical-align:-0.3499303pt" id="M4" height="7.35473pt" version="1.1" viewBox="-0.0498162 -7.0048 7.75925 7.35473" width="7.75925pt"><g transform="matrix(.013,0,0,-0.013,0,0)"><use xlink:href="#g117-37"/></g></svg> 4.6 mm. The error was typically higher if less CA was used. A combination of both similarity measures outperforms a previously proposed similarity measure. The mean accuracy for well contrasted sequences is in the range of other proposed manual registration methods.

Matthias Hoffmann

Christopher Kowalewski

Andreas Maier

Klaus Kurzidim

Norbert Strobel

Joachim Hornegger

Contrast-Based 3D/2D Registration of the Left Atrium: Fast versus Consistent

<i>Purpose</i>. To develop a method for identifying abnormal myocardial function based on studying the normalized wall motion pattern during the cardiac cycle.<i> Methods</i>. The temporal pattern of the normalized myocardial wall thickness is used as a feature vector to assess the cardiac wall motion abnormality. Principal component analysis is used to reduce the feature dimensionality and the maximum likelihood method is used to differentiate between normal and abnormal features. The proposed method was applied on a dataset of 27 cases from normal subjects and patients.<i> Results</i>. The developed method achieved 81.5&#x25;, 85&#x25;, and 88.5&#x25; accuracy for identifying abnormal contractility in the basal, midventricular, and apical slices, respectively.<i> Conclusions</i>. A novel feature vector, namely, the normalized wall thickness, has been introduced for detecting myocardial regional wall motion abnormality. The proposed method provides assessment of the regional myocardial contractility for each cardiac segment and slice; therefore, it could be a valuable tool for automatic and fast determination of regional wall motion abnormality from conventional cine MRI images.

Mai Wael

El-Sayed H. Ibrahim

Ahmed S. Fahmy

Detection of Cardiac Function Abnormality from MRI Images Using Normalized Wall Thickness Temporal Patterns

An integrate fabrication framework is presented to build heterogeneous objects (HEO) using digital microdroplets injecting technology and rapid prototyping. The heterogeneous materials part design and manufacturing method in structure and material was used to change the traditional process. The net node method was used for digital modeling that can configure multimaterials in time. The relationship of material, color, and jetting nozzle was built. The main important contributions are to combine the structure, material, and visualization in one process and give the digital model for manufacture. From the given model, it is concluded that the method is effective for HEO. Using microdroplet rapid prototyping and the model given in the paper HEO could be gotten basically. The model could be used in 3D biomanufacturing.

Na Li

Chunmei Feng

Liya Zhu

Aiqing Guo

Digital Microdroplet Ejection Technology-Based Heterogeneous Objects Prototyping

With the advancement of technology in communication network, it facilitated digital medical images transmitted to healthcare professionals via internal network or public network (e.g., Internet), but it also exposes the transmitted digital medical images to the security threats, such as images tampering or inserting false data in the images, which may cause an inaccurate diagnosis and treatment. Medical image distortion is not to be tolerated for diagnosis purposes; thus a digital watermarking on medical image is introduced. So far most of the watermarking research has been done on single frame medical image which is impractical in the real environment. In this paper, a digital watermarking on multiframes medical images is proposed. In order to speed up multiframes watermarking processing time, a parallel watermarking processing on medical images processing by utilizing multicores technology is introduced. An experiment result has shown that elapsed time on parallel watermarking processing is much shorter than sequential watermarking processing.

Hui Liang Khor

Siau-Chuin Liew

Jasni Mohd. Zain

Parallel Digital Watermarking Process on Ultrasound Medical Images in Multicores Environment

This paper presents an automatic lesion segmentation method based on similarities between multichannel patches. A patch database is built using training images for which the label maps are known. For each patch in the testing image, <svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" style="vertical-align:-0.2063999pt" id="M1" height="9.49473pt" version="1.1" viewBox="-0.0498162 -9.28833 6.66314 9.49473" width="6.66314pt"><g transform="matrix(.013,0,0,-0.013,0,0)"><path id="g113-108" d="M480 416C480 431 465 448 438 448C388 448 312 383 252 330C217 299 188 273 155 237H153L257 680C262 700 263 712 253 712C240 712 183 684 97 674L92 648L126 647C166 646 172 645 163 606L23 -6L29 -12C51 -5 77 2 107 8C115 62 130 128 142 180C153 193 179 220 204 241C231 170 259 106 288 54C317 0 336 -12 358 -12C381 -12 423 2 477 80L460 100C434 74 408 54 398 54C385 54 374 65 351 107C326 154 282 241 263 299C296 332 351 377 403 377C424 377 436 372 445 368C449 366 456 368 462 375C472 386 480 402 480 416Z"/></g></svg> similar patches are retrieved from the database. The matching labels for these <svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" style="vertical-align:-0.2063999pt" id="M2" height="9.49473pt" version="1.1" viewBox="-0.0498162 -9.28833 6.66314 9.49473" width="6.66314pt"><g transform="matrix(.013,0,0,-0.013,0,0)"><use xlink:href="#g113-108"/></g></svg> patches are then combined to produce an initial segmentation map for the test case. Finally an iterative patch-based label refinement process based on the initial segmentation map is performed to ensure the spatial consistency of the detected lesions. The method was evaluated in experiments on multiple sclerosis (MS) lesion segmentation in magnetic resonance images (MRI) of the brain. An evaluation was done for each image in the MICCAI 2008 MS lesion segmentation challenge. Results are shown to compete with the state of the art in the challenge. We conclude that the proposed algorithm for segmentation of lesions provides a promising new approach for local segmentation and global detection in medical images.

Roey Mechrez

Jacob Goldberger

Hayit Greenspan

Patch-Based Segmentation with Spatial Consistency: Application to MS Lesions in Brain MRI

Alzheimer&#x2019;s disease is a complex neurodegenerative disease affecting millions of individuals worldwide. Earlier it was diagnosed only via clinical assessments and confirmed by postmortem brain histopathology. The development of validated biomarkers for Alzheimer&#x2019;s disease has given impetus to improve diagnostics and accelerate the development of new therapies. Functional imaging like positron emission tomography (PET), single photon emission computed tomography (SPECT), functional magnetic resonance imaging (fMRI), and proton magnetic resonance spectroscopy provides a means of detecting and characterising the regional changes in brain blood flow, metabolism, and receptor binding sites that are associated with Alzheimer&#x2019;s disease. Multimodal neuroimaging techniques have indicated changes in brain structure and metabolic activity, and an array of neurochemical variations that are associated with neurodegenerative diseases. Radiotracer-based PET and SPECT potentially provide sensitive, accurate methods for the early detection of disease. This paper presents a review of neuroimaging modalities like PET, SPECT, and selected imaging biomarkers/tracers used for the early diagnosis of AD. Neuroimaging with such biomarkers and tracers could achieve a much higher diagnostic accuracy for AD and related disorders in the future.

Abishek Arora

Neeta Bhagat

Insight into the Molecular Imaging of Alzheimer&#x2019;s Disease

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<p><em>International Journal of Biomedical Imaging</em> aims to promote research and development of biomedical imaging by publishing high-quality research articles and reviews in this rapidly growing interdisciplinary field.</p>


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International Journal of Biomedical Imaging - Table of contents 2016

International Journal of Biomedical Imaging | Hindawi

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International Journal of Biomedical Imaging aims to promote research and development of biomedical imaging by publishing high-quality research articles and reviews in this rapidly growing interdisciplinary field.

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International Journal of Biomedical Imaging

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International Journal of Biomedical Imaging