Evaluation of a processing scheme for calcified atheromatous carotid artery detection in face/neck CBCT images

Carotid duplex sonography is a useful method for evaluation of dural arteriovenous fistulas. The resistance index of the external carotid artery has been reported to correlate with the efficacy of treatment and recurrence or aggravation of dural arteriovenous fistulas. Herein, we describe a case of dural arteriovenous fistulas mainly supplied by the occipital artery and show that the resistance index of the occipital artery was more sensitive than that of the external carotid artery. To the best of our knowledge, this is the first report to describe the feasibility of occipital artery detection by carotid duplex sonography and clinical application of the resistance index of the occipital artery for dural arteriovenous fistulas.

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Automatic Carotid Artery Detection Using Attention Layer Region-Based Convolution Neural Network

International Journal of Humanoid Robotics ◽

10.1142/s0219843619500154 ◽

2019 ◽

Vol 16 (04) ◽

pp. 1950015

Author(s):

Xiaoyan Wang ◽

Xingyu Zhong ◽

Ming Xia ◽

Weiwei Jiang ◽

Xiaojie Huang ◽

...

Keyword(s):

Carotid Artery ◽

Object Detection ◽

State Of The Art ◽

Region Of Interest ◽

Feature Maps ◽

Interactive Approach ◽

Detection Systems ◽

Art Object ◽

Layer Region ◽

Artery Detection

Localization of vessel Region of Interest (ROI) from medical images provides an interactive approach that can assist doctors in evaluating carotid artery diseases. Accurate vessel detection is a prerequisite for the following procedures, like wall segmentation, plaque identification and 3D reconstruction. Deep learning models such as CNN have been widely used in medical image processing, and achieve state-of-the-art performance. Faster R-CNN is one of the most representative and successful methods for object detection. Using outputs of feature maps in different layers has been proved to be a useful way to improve the detection performance, however, the common method is to ensemble outputs of different layers directly, and the special characteristic and different importance of each layer haven’t been considered. In this work, we introduce a new network named Attention Layer R-CNN(AL R-CNN) and use it for automatic carotid artery detection, in which we integrate a new module named Attention Layer Part (ALP) into a basic Faster R-CNN system for better assembling feature maps of different layers. Experimental results on carotid dataset show that our method surpasses other state-of-the-art object detection systems.

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Endotoxin Alteration of the Mucopolysaccharide Blood Vessel Coating in Rats

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100050755 ◽

1974 ◽

Vol 32 ◽

pp. 148-149

Author(s):

D. E. Philpott ◽

A. Takahashi

Keyword(s):

Skeletal Muscle ◽

Endothelial Cells ◽

Salivary Gland ◽

Carotid Artery ◽

Basement Membrane ◽

Coronary Vessels ◽

Ruthenium Red ◽

E Coli ◽

Old Rats ◽

The Brain

Two month, eight month and two year old rats were treated with 10 or 20 mg/kg of E. Coli endotoxin I. P. The eight month old rats proved most resistant to the endotoxin. During fixation the aorta, carotid artery, basil arartery of the brain, coronary vessels of the heart, inner surfaces of the heart chambers, heart and skeletal muscle, lung, liver, kidney, spleen, brain, retina, trachae, intestine, salivary gland, adrenal gland and gingiva were treated with ruthenium red or alcian blue to preserve the mucopolysaccharide (MPS) coating. Five, 8 and 24 hrs of endotoxin treatment produced increasingly marked capillary damage, disappearance of the MPS coating, edema, destruction of endothelial cells and damage to the basement membrane in the liver, kidney and lung.

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