Robust Nanoparticles Detection From Noisy Background by Fusing Complementary Image Information

2016 ◽  
Vol 25 (12) ◽  
pp. 5713-5726 ◽  
Author(s):  
Yanjun Qian ◽  
Jianhua Z. Huang ◽  
Xiaodong Li ◽  
Yu Ding
Keyword(s):  
Image Information ◽  
Complementary Image ◽  
Nanoparticles Detection ◽  
Noisy Background

Pseudo-Dynamic Fault Isolation Technique Using Backside Emission Microscopy – Case Study, Where All Other Methods Fail

2002 ◽  
Author(s):  
Yoav Weizman ◽  
Ezra Baruch ◽  
Michael Zimin
Keyword(s):  
Failure Analysis ◽  
Process Variations ◽  
Fault Isolation ◽  
Operating Conditions ◽  
Detection Sensitivity ◽  
Isolation Technique ◽  
Root Cause ◽  
Emission Microscopy ◽  
Failure Location ◽  
Noisy Background

Abstract Emission microscopy is usually implemented for static operating conditions of the DUT. Under dynamic operation it is nearly impossible to identify a failure out of the noisy background. In this paper we describe a simple technique that could be used in cases where the temporal location of the failure was identified however the physical location is not known or partially known. The technique was originally introduced to investigate IDDq failures (1) in order to investigate timing related issues with automated tester equipment. Ishii et al (2) improved the technique and coupled an emission microscope to the tester for functional failure analysis of DRAMs and logic LSIs. Using consecutive step-by-step tester halting coupled to a sensitive emission microscope, one is able detect the failure while it occurs. We will describe a failure analysis case in which marginal design and process variations combined to create contention at certain logic states. Since the failure occurred arbitrarily, the use of the traditional LVP, that requires a stable failure, misled the analysts. Furthermore, even if we used advanced tools as PICA, which was actually designed to locate such failures, we believe that there would have been little chance of observing the failure since the failure appeared only below 1.3V where the PICA tool has diminished photon detection sensitivity. For this case the step-by-step halting technique helped to isolate the failure location after a short round of measurements. With the use of logic simulations, the root cause of the failure was clear once the failing gate was known.

Application of Intelligent Facial Dynamic Information Image in Warm Acupuncture and Moxibustion on Peripheral Facial Paralysis (Preprint)

2020 ◽  
Author(s):  
Yanping Chen ◽  
Dongjie Yu ◽  
Jane Cansoni
Keyword(s):  
Facial Paralysis ◽  
Computer Technology ◽  
Treatment Time ◽  
Facial Features ◽  
Nerve Function ◽  
Facial Nerve Function ◽  
Peripheral Facial Paralysis ◽  
Image Information ◽  
Dynamic Image ◽  
Acupuncture And Moxibustion

BACKGROUND Background: Nowadays, the application of computer technology in the medical field is more and more extensive, and many diseases can achieve better diagnosis and treatment effects through computer technology. OBJECTIVE Objective: The paper applies intelligent facial dynamic image information to the clinical treatment of peripheral acupuncture and moxibustion for the treatment of peripheral facial paralysis. An automatic acupoint positioning algorithm based on facial information dynamic image is proposed, which provides an objective and standard basis for the treatment of facial acupuncture and moxibustion. METHODS Methods: The paper selects the head threshold, that is, the facial dynamic image information as the research background, and divides the facial features according to the "three courts and five eyes" rule, and uses the Minimum Eigenvalue operator to detect the corner points of the facial features, locate the facial features, and use the face. The feature position is used as a reference coordinate for facial acupoint positioning. RESULTS Results: After verification, it was found that the positioning was accurate, and the peripheral facial paralysis of the patient was improved after warm acupuncture point positioning treatment, which improved the facial nerve function of the patient, improved the treatment efficiency and shortened the treatment time. Therefore, this technology is worthy of clinical promotion. CONCLUSIONS Conclusion: Through experimental analysis, the algorithm is proved to be effective and accurate. Based on facial dynamic image information to locate acupoints, warm acupuncture has a significant effect on peripheral facial paralysis, which can significantly improve facial nerve function and shorten treatment time, which is worthy of clinical promotion.

scholarly journals Fully-automated root image analysis (faRIA)

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Narendra Narisetti ◽  
Michael Henke ◽  
Christiane Seiler ◽  
Astrid Junker ◽  
Jörn Ostermann ◽  
...  
Keyword(s):  
Near Infrared ◽  
Climatic Factors ◽  
Plant Root ◽  
Ground Truth ◽  
Parameter Tuning ◽  
Dice Coefficient ◽  
Powerful Analytical Tool ◽  
Manual Interaction ◽  
And Function ◽  
Noisy Background

AbstractHigh-throughput root phenotyping in the soil became an indispensable quantitative tool for the assessment of effects of climatic factors and molecular perturbation on plant root morphology, development and function. To efficiently analyse a large amount of structurally complex soil-root images advanced methods for automated image segmentation are required. Due to often unavoidable overlap between the intensity of fore- and background regions simple thresholding methods are, generally, not suitable for the segmentation of root regions. Higher-level cognitive models such as convolutional neural networks (CNN) provide capabilities for segmenting roots from heterogeneous and noisy background structures, however, they require a representative set of manually segmented (ground truth) images. Here, we present a GUI-based tool for fully automated quantitative analysis of root images using a pre-trained CNN model, which relies on an extension of the U-Net architecture. The developed CNN framework was designed to efficiently segment root structures of different size, shape and optical contrast using low budget hardware systems. The CNN model was trained on a set of 6465 masks derived from 182 manually segmented near-infrared (NIR) maize root images. Our experimental results show that the proposed approach achieves a Dice coefficient of 0.87 and outperforms existing tools (e.g., SegRoot) with Dice coefficient of 0.67 by application not only to NIR but also to other imaging modalities and plant species such as barley and arabidopsis soil-root images from LED-rhizotron and UV imaging systems, respectively. In summary, the developed software framework enables users to efficiently analyse soil-root images in an automated manner (i.e. without manual interaction with data and/or parameter tuning) providing quantitative plant scientists with a powerful analytical tool.

Damage Assessment of the Attacked Airports Based on Image Analysis

2013 ◽  
Vol 321-324 ◽  
pp. 1168-1171
Author(s):  
Xiao Nan Zhang ◽  
Jun Feng Yang ◽  
Si Liang Du ◽  
Jun Zhi
Keyword(s):  
Damage Assessment ◽  
Automatic Method ◽  
Analysis Method ◽  
Image Information ◽  
Damage Degree ◽  
Before And After ◽  
Battle Damage Assessment ◽  
Damage Extent ◽  
Modern War ◽  
Assessment Result

Battle Damage Assessment (BDA) is to assess the damage degree of enemy’s target after being attacked. In modern war, combat commanders always make decision on the basis of BDA. In this paper, an automatic method for assessing the damage extent of an attacked airport based on the image taken before and after a strike is described. Firstly, the airport blockade condition is analyzed and damage assessment criteria of airport are proposed. Secondly, three steps of the image information pretreatment are carried out and a reliability analysis method of image information is proposed. Lastly, damage assessment result is calculated to verify the validity and availability of the proposed method.

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