ULTRASOUND VOLUME RECONSTRUCTION BASED ON DIRECT FRAME INTERPOLATION

Author(s):  
Sergei Koptenko ◽  
Rachel Remlinger ◽  
Martin Lachaine ◽  
Tony Falco ◽  
Ulrich Scheipers
2010 ◽  
Vol 57 (11) ◽  
pp. 2460-2470 ◽  
Author(s):  
Ulrich Scheipers ◽  
Sergei Koptenko ◽  
Rachel Remlinger ◽  
Tony Falco ◽  
Martin Lachaine

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yongcheol Kim ◽  
Jonathan James Hyett Bray ◽  
Benjamin Waterhouse ◽  
Alexander Gall ◽  
Georgia May Connolly ◽  
...  

AbstractNon-atherosclerotic abnormalities of vessel calibre, aneurysm and ectasia, are challenging to quantify and are often overlooked in qualitative reporting. Utilising a novel 3-dimensional (3D) quantitative coronary angiography (QCA) application, we have evaluated the characteristics of normal, diabetic and aneurysmal or ectatic coronary arteries. We selected 131 individuals under 50 years-of-age, who had undergone coronary angiography for suspected myocardial ischaemia between 1st January 2011 and 31st December 2015, at the Bristol Heart Institute, Bristol, UK. This included 42 patients with angiographically normal coronary arteries, 36 diabetic patients with unobstructed coronaries, and 53 patients with abnormal coronary dilatation (aneurysm and ectasia). A total of 1105 coronary segments were analysed using QAngio XA 3D (Research Edition, Medis medical imaging systems, Leiden, The Netherlands). The combined volume of the major coronary arteries was significantly different between each group (1240 ± 476 mm3 diabetic group, 1646 ± 391 mm3 normal group, and 2072 ± 687 mm3 abnormal group). Moreover, the combined coronary artery volumes correlated with patient body surface area (r = 0.483, p < 0.01). Inter-observer variability was assessed and intraclass correlation coefficient of the total coronary artery volume demonstrated a low variability of 3D QCA (r = 0.996, p < 0.001). Dedicated 3D QCA facilitates reproducible coronary artery volume estimation and allows discrimination of normal and diseased vessels.


2021 ◽  
Vol 69 ◽  
pp. 101957
Author(s):  
Rewa R. Sood ◽  
Wei Shao ◽  
Christian Kunder ◽  
Nikola C. Teslovich ◽  
Jeffrey B. Wang ◽  
...  

2020 ◽  
Vol 34 (07) ◽  
pp. 10607-10614 ◽  
Author(s):  
Xianhang Cheng ◽  
Zhenzhong Chen

Learning to synthesize non-existing frames from the original consecutive video frames is a challenging task. Recent kernel-based interpolation methods predict pixels with a single convolution process to replace the dependency of optical flow. However, when scene motion is larger than the pre-defined kernel size, these methods yield poor results even though they take thousands of neighboring pixels into account. To solve this problem in this paper, we propose to use deformable separable convolution (DSepConv) to adaptively estimate kernels, offsets and masks to allow the network to obtain information with much fewer but more relevant pixels. In addition, we show that the kernel-based methods and conventional flow-based methods are specific instances of the proposed DSepConv. Experimental results demonstrate that our method significantly outperforms the other kernel-based interpolation methods and shows strong performance on par or even better than the state-of-the-art algorithms both qualitatively and quantitatively.


2015 ◽  
Vol 75 (2) ◽  
Author(s):  
Ho Wei Yong ◽  
Abdullah Bade ◽  
Rajesh Kumar Muniandy

Over the past thirty years, a number of researchers have investigated on 3D organ reconstruction from medical images and there are a few 3D reconstruction software available on the market. However, not many researcheshave focused on3D reconstruction of breast cancer’s tumours. Due to the method complexity, most 3D breast cancer’s tumours reconstruction were done based on MRI slices dataeven though mammogram is the current clinical practice for breast cancer screening. Therefore, this research will investigate the process of creating a method that will be able to reconstruct 3D breast cancer’s tumours from mammograms effectively.  Several steps were proposed for this research which includes data acquisition, volume reconstruction, andvolume rendering. The expected output from this research is the 3D breast cancer’s tumours model that is generated from correctly registered mammograms. The main purpose of this research is to come up with a 3D reconstruction method that can produce good breast cancer model from mammograms while using minimal computational cost.


2006 ◽  
Vol 154 (2) ◽  
pp. 144-167 ◽  
Author(s):  
Albert Lawrence ◽  
James C. Bouwer ◽  
Guy Perkins ◽  
Mark H. Ellisman

Sign in / Sign up

Export Citation Format

Share Document