Journal: Journal of Cardiovascular Development and Disease

Article Title: The Role of Cardiac Magnetic Resonance in Characterizing Atrial Cardiomyopathy and Guiding Substrate Ablation in Atrial Fibrillation: A Narrative Review

doi: 10.3390/jcdd12040114

Figure Lengend Snippet: Atrial CMR imaging post-processing protocol adopted in the most relevant studies evaluating MRI-guided AF ablation.

Article Snippet: Akoum/2015/monocentric, retrospective observational study [ ] , Left atrial wall volumes were manually segmented from the LGE-MRI by expert observers using the Coreview image processing software (Marrek Inc.); the resulting LA wall segmentation included the 3D extent of both the LA wall and the antral regions of the PVs. Fibrosis regions in the LGE-MRI were identified based on an intensity threshold established through expert evaluation. A volume-rendering tool in Corview enabled operators to visualize enhancement distribution in 3D; a custom transfer function was employed to define enhancement gradations while suppressing blood and normal tissue. Fibrosis and scarring were reported as a percentage of the atrial wall; patients were categorized into four stages (Utah stages) based on their baseline fibrosis..

Techniques: Imaging, Software, Standard Deviation

Journal: Medical image analysis

Article Title: Intra-retinal layer segmentation of 3D optical coherence tomography using coarse grained diffusion map

doi: 10.1016/j.media.2013.05.006

Figure Lengend Snippet: A brief look at different approaches in OCT segmentation. It should be noticed that the number as reported cannot be used for direct comparison of the relative performances, since different settings are utilized in each method.

Article Snippet: While there is no theoretical limit on the number of layers that can be simultaneously segmented by these approaches, up to 10 layers are routinely identified in retinal OCT images. gives an overview of the mentioned approaches and compares the OCT systems, preprocessing methods, error ranges and computation times. table ft1 table-wrap mode="anchored" t5 caption a7 Segmentation approach Papers OCT systems Preprocessing method Error range Computation time A-scan Hee et al. (1995) , Huang et al. (1991) , George et al. (2000) , Koozekanani et al. (2001) , Gregori and Knighton (2004) , Herzog et al. (2004) , Shahidi et al. (2005) , Ishikawa et al. (2005) , Srinivasan et al. (2008) , Fabritius et al. (2009) , Koprowski and Wrobel (2009) , Lu et al. (2010) , and Mayer et al. (2010) TD-OCT (Humphrey 2000, Stratus, OCT 3 Carl- Zeiss Meditec)/SD OCT (Cirrus HD- OCT) Low-pass filtering, 2D linear smoothing, median filter, non- linear anisotropic filter, Intensity signal based thresholding segmentation 20–36 lm and around 5 pixels in recent papers Not reported in older cases, but in recent ones like Fabritius et al. (2009) , required about 17–21 s for each boundary using a PC With 2.4 GHz CPU, 2.93 GB RAM Intensity based B-scan analysis Boyer et al. (2006) , Baroni et al. (2007) , Tan et al. (2008) , Bagci et al. (2008) , and Kajić et al. (2010) TD OCT (OCT 3000 Zees-Humphrey, OCT 2 Carl-Zeiss Meditec, Stratus)/ SDOCT (RTVue100 OCT, Optovue, Freemont, CA) 2D median filter, Gaussian smoothing filtering, bilateral filter 4.2–5 μm 9 s For each image on a Pentium, 1.8 GHz processor with1 GB of RAM Active contours Cabrera Fernández et al. (2004) , Mishra et al. (2009) , Yazdanpanah et al. (2009) , and Mujat et al. (2005) TD OCT (Stratus OCT)/ experimental HR OCT (high speed) / experimental FD- OCT Nonlinear anisotropic diffusion filter, adaptive vector-valued kernel function Around 10 μm 5–84 s for each image using Pentium 4 CPU, 2.26 GHz Artificial intelligence Fuller et al. (2007) and Mayer et al. (2008) Experimental 3D OCT, SD OCT (Spectralis) SVM approach, 2D mean filter, directional filtering Around 18 μm 45–120 s on a 2 GHz Pentium IV on a computer with 3 GB of RAM (dual processor 3 GHz Intel Xeon) 2D or 3D graphs Garvin et al. (2008) , Abràmoff et al. (2009) , Lee et al. (2010) , Yang et al. (2010) , Quellec et al. (2010) , Chiu et al. (2012) , and Chiu et al. (2010) TD OCT (Stratus OCT)/SD OCT (Cirrus–OCT Topcon 3D OCT- 1000) 2D spectral reducing anisotropic diffusion filter, median filtering, wavelets 2.8–6.1 μm In 2D approach, 9.74 s per image (64-bit OS, Intel Core2 Duo CPU at 2.53 GHz, and 4 GB RAM).

Techniques: Diffusion-based Assay, Plasmid Preparation