A System for Real-Time, Online Mixed-Reality Visualization of Cardiac Magnetic Resonance Images

Image-guided cardiovascular interventions are rapidly evolving procedures that necessitate imaging systems capable of rapid data acquisition and low-latency image reconstruction and visualization. Compared to alternative modalities, Magnetic Resonance Imaging (MRI) is attractive for guidance in complex interventional settings thanks to excellent soft tissue contrast and large fields-of-view without exposure to ionizing radiation. However, most clinically deployed MRI sequences and visualization pipelines exhibit poor latency characteristics, and spatial integration of complex anatomy and device orientation can be challenging on conventional 2D displays. This work demonstrates a proof-of-concept system linking real-time cardiac MR image acquisition, online low-latency reconstruction, and a stereoscopic display to support further development in real-time MR-guided intervention. Data are acquired using an undersampled, radial trajectory and reconstructed via parallelized through-time radial generalized autocalibrating partially parallel acquisition (GRAPPA) implemented on graphics processing units. Images are rendered for display in a stereoscopic mixed-reality head-mounted display. The system is successfully tested by imaging standard cardiac views in healthy volunteers. Datasets comprised of one slice (46 ms), two slices (92 ms), and three slices (138 ms) are collected, with the acquisition time of each listed in parentheses. Images are displayed with latencies of 42 ms/frame or less for all three conditions. Volumetric data are acquired at one volume per heartbeat with acquisition times of 467 ms and 588 ms when 8 and 12 partitions are acquired, respectively. Volumes are displayed with a latency of 286 ms or less. The faster-than-acquisition latencies for both planar and volumetric display enable real-time 3D visualization of the heart.

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Semantic Edge Detection for Tracking Vocal Tract Air-Tissue Boundaries in Real-Time Magnetic Resonance Images

10.21437/interspeech.2017-1580 ◽

2017 ◽

Cited By ~ 12

Author(s):

Krishna Somandepalli ◽

Asterios Toutios ◽

Shrikanth S. Narayanan

Keyword(s):

Magnetic Resonance ◽

Edge Detection ◽

Real Time ◽

Vocal Tract ◽

Magnetic Resonance Images

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Visualization of Cartilage from Knee Joint Magnetic Resonance Images and Quantitative Assessment to Study the Effect of Age, Gender and Body Mass Index (BMI) in Progressive Osteoarthritis (OA)

Current Medical Imaging Formerly Current Medical Imaging Reviews ◽

10.2174/1573405614666181018123251 ◽

2019 ◽

Vol 15 (6) ◽

pp. 565-572

Author(s):

Mallikarjunaswamy Shivagangadharaiah Matada ◽

Mallikarjun Sayabanna Holi ◽

Rajesh Raman ◽

Sujana Theja Jayaramu Suvarna

Keyword(s):

Body Mass Index ◽

Magnetic Resonance ◽

Knee Joint ◽

Body Mass ◽

3D Visualization ◽

Cartilage Degradation ◽

Magnetic Resonance Images ◽

Cartilage Thickness ◽

Knee Joints ◽

Data Set

Background: Osteoarthritis (OA) is a degenerative disease of joint cartilage affecting the elderly people around the world. Visualization and quantification of cartilage is very much essential for the assessment of OA and rehabilitation of the affected people. Magnetic Resonance Imaging (MRI) is the most widely used imaging modality in the treatment of knee joint diseases. But there are many challenges in proper visualization and quantification of articular cartilage using MRI. Volume rendering and 3D visualization can provide an overview of anatomy and disease condition of knee joint. In this work, cartilage is segmented from knee joint MRI, visualized in 3D using Volume of Interest (VOI) approach. Methods: Visualization of cartilage helps in the assessment of cartilage degradation in diseased knee joints. Cartilage thickness and volume were quantified using image processing techniques in OA affected knee joints. Statistical analysis is carried out on processed data set consisting of 110 of knee joints which include male (56) and female (54) of normal (22) and different stages of OA (88). The differences in thickness and volume of cartilage were observed in cartilage in groups based on age, gender and BMI in normal and progressive OA knee joints. Results: The results show that size and volume of cartilage are found to be significantly low in OA as compared to normal knee joints. The cartilage thickness and volume is significantly low for people with age 50 years and above and Body Mass Index (BMI) equal and greater than 25. Cartilage volume correlates with the progression of the disease and can be used for the evaluation of the response to therapies. Conclusion: The developed methods can be used as helping tool in the assessment of cartilage degradation in OA affected knee joint patients and treatment planning.

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Automatic Registration between Real-Time Ultrasonography and Pre-Procedural Magnetic Resonance Images: A Prospective Comparison between Two Registration Methods by Liver Surface and Vessel and by Liver Surface Only

Ultrasound in Medicine & Biology ◽

10.1016/j.ultrasmedbio.2016.02.008 ◽

2016 ◽

Vol 42 (7) ◽

pp. 1627-1636 ◽

Cited By ~ 7

Author(s):

Ah Yeong Kim ◽

Min Woo Lee ◽

Dong Ik Cha ◽

Hyo Keun Lim ◽

Young-Taek Oh ◽

...

Keyword(s):

Magnetic Resonance ◽

Real Time ◽

Magnetic Resonance Images ◽

Automatic Registration ◽

Prospective Comparison ◽

Liver Surface ◽

Real Time Ultrasonography

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Implementation of Iterative bilateral filtering for removal of Rician noise in MR images using FPGA

International Journal of Recent Technology and Engineering - 2 ◽

10.35940/ijrte.c4351.099320 ◽

2020 ◽

Vol 9 (3) ◽

pp. 279-284

Keyword(s):

Magnetic Resonance ◽

Real Time ◽

Visual Analysis ◽

Similarity Index ◽

Structural Similarity ◽

Bilateral Filter ◽

Magnetic Resonance Images ◽

Rician Noise ◽

Diagnostic Quality ◽

Index Matrix

Magnetic resonance image noise reduction is important to process further and visual analysis. Bilateral filter is denoises image and also preserves edge. It proposes Iterative bilateral filter which reduces Rician noise in the magnitude magnetic resonance images and retains the fine structures, edges and it also reduces the bias caused by Rician noise. The visual and diagnostic quality of the image is retained. The quantitative analysis is based on analysis of standard quality metrics parameters like peak signal-to-noise ratio and mean structural similarity index matrix reveals that these methods yields better results than the other proposed denoising methods for MRI. Problem associated with the method is that it is computationally complex hence time consuming. It is not recommended for real time applications. To use in real time application a parallel implantation of the same using FPGA is proposed.

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Semi-automatic method for analysing vocal tract morphology from real-time magnetic resonance images

10.31234/osf.io/y6xde ◽

2021 ◽

Author(s):

Michel Belyk ◽

Christopher Carignan ◽

Carolyn McGettigan

Keyword(s):

Magnetic Resonance ◽

Real Time ◽

Vocal Tract ◽

Structural Features ◽

Magnetic Resonance Images ◽

Training Data ◽

Surrounding Tissue ◽

User Input ◽

Internal Structures ◽

Automated Processing

Real-time magnetic resonance imaging is a technique that provides high contrast videographic data of the vocal tract that allow researchers to observe the internal structures that shape the sounds of speech. However, structural features need to be extracted from these vocal tract images to make them useful to researchers. We have developed a semi-automated processing pipeline that produces outlines of the vocal tract to quantify vocal tract morphology. Our approach uses simple tissue classification constrained to pixels that analysts have identified as likely to contain the vocal tract and surrounding tissue. This approach is supplemented with multiple opportunities for the analyst to intervene in order to ensure that outputs are robust to errors. Although this approach is more labour intensive than more fully automated alternatives, these costs are offset by the benefits of improving the quality of measurements. We demonstrate that this pipeline can be generalised to a range of datasets and that it remains reliable across analysts, particularly among analysts with vocal tract expertise. The pipeline’s reliance on user input presents a challenge to scalability if applied to very large. Measurements produced by this pipeline could be provide a broader scope of training data for fully automated methods in an effort to improve their generalisability.

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Treatment of hepatocellular carcinoma using the Smart Fusion needle navigation system: conversion from real-time 4D-echo data

Open Journal of Gastroenterology and Hepatology ◽

10.28933/ojgh-2021-02-1005 ◽

2021 ◽

pp. 46

Author(s):

Keyword(s):

Hepatocellular Carcinoma ◽

Magnetic Resonance ◽

Real Time ◽

Navigation System ◽

Magnetic Resonance Images ◽

The Body ◽

Target Point ◽

Ultrasound Images ◽

Volume Data ◽

Needle Position

Advances in ultrasound systems have improved the accuracy of hepatocellular carcinoma (HCC) diagnosis and treatment. We have been treating HCC using real-time 4D and Live 3D-echo technologies. However, these treatment methods have drawbacks such as vibrations during puncture and a limited angle of needle insertion. To overcome these problems, systems that can display ultrasound images simultaneously with computed tomography (CT) and magnetic resonance images in a real-time manner for reference purposes have been reported. These systems have recently been equipped with a needle tip navigation system, making it possible to reliably visualize tumors and determine the needle tip position in a tumor. These developments have enabled the safe treatment of HCC. Treatment using needle navigation is performed as follows: A Canon APLIO800 ultrasound system is used with a conventional convex probe (PVT-375BT) and a micro-convex probe (PVT-382BT). The system function is known as Smart Fusion. Ultrasound images can be displayed with volume data from other modalities, such as CT and magnetic resonance imaging (MRI), in relation to the positional information using a magnetic sensor. This enables the use of CT/MRI data as reference for accurate puncture and treatment of lesions that are difficult to identify by ultrasound alone. Axis alignment is also completed by displaying the xiphoid process on a CT image and having the system learn the orientation of the probe placed perpendicular to the body axis. Then, landmark alignment is performed and fine-adjusted by aligning a target point near the lesion with the same point as displayed on CT (Fig. 1). Case presentation A 7x-year-old woman was found to have elevated tumor markers and a liver tumor identified by regular blood testing and CT performed in August 20xx and was admitted to our hospital for treatment. Abdominal ultrasonography showed a hypoechoic lesion measuring approximately 3 cm in diameter in liver S6, which led to a diagnosis of HCC. For treatment, microwave therapy was selected at the patient’s request. Microwaves were delivered using a Medtronic Emprint ablation system with a 3.0-cm needle for ablation. During treatment, the needle position was confirmed by needle navigation before ablation (Fig. 2) because the tumor needed to be ablated in an overlapping manner (Fig. 3).

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