scholarly journals Comparison of Two Ultra-Widefield Cameras With High Image Resolution and Wider View for Identifying Diabetic Retinopathy Lesions

2021 ◽  
Vol 10 (12) ◽  
pp. 9
Author(s):  
Rehana Khan ◽  
Sundaresan Raman ◽  
Sri Krishna M. Karamcheti ◽  
Sangeetha Srinivasan ◽  
Abhishek Sharma ◽  
...  
Keyword(s):  
Diabetic Retinopathy ◽  
Image Resolution ◽  
High Image Resolution

Methodology for TEM Analysis of Barrier Profiles

2002 ◽  
Author(s):  
Tan-Chen Lee ◽  
Jui-Yen Huang ◽  
Li-Chien Chen ◽  
Ruey-Lian Hwang ◽  
David Su
Keyword(s):  
Sample Preparation ◽  
Profile Analysis ◽  
Image Interpretation ◽  
Sample Thickness ◽  
Image Resolution ◽  
Specimen Preparation ◽  
Tem Analysis ◽  
Preparation Methods ◽  
High Image Resolution ◽  
Common Technique

Abstract Device shrinkage has resulted in thinner barriers and smaller vias. Transmission Electron Microscopy (TEM) has become a common technique for barrier profile analysis because of its high image resolution. TEM sample preparation and image interpretation becomes difficult when the size of the small cylindrical via is close to the TEM sample thickness. Effects of different sample thickness and specimen preparation methods, therefore, have been investigated. An automatic FIB program has been shown to be useful in via sample preparation. Techniques for imaging a TEM specimen will be discussed in the paper. Conventional TEM bright field (BF) image is adequate to examine the barrieronly via; however, other techniques are more suitable for a Cu filled via.

scholarly journals Differences in the Tensor Veli Palatini Muscle and Hearing Status in Children With and Without 22q11.2 Deletion Syndrome

2019 ◽  
Vol 57 (3) ◽  
pp. 302-309
Author(s):  
Jamie L. Perry ◽  
Katelyn J. Kotlarek ◽  
Kelly Spoloric ◽  
Adriane Baylis ◽  
Lakshmi Kollara ◽  
...  
Keyword(s):  
Three Dimensional ◽  
Muscle Length ◽  
22Q11.2 Deletion Syndrome ◽  
Image Resolution ◽  
Deletion Syndrome ◽  
22Q11.2 Deletion ◽  
3 Dimensional ◽  
High Image Resolution ◽  
Tensor Veli Palatini Muscle ◽  
Magnetic Resonance Imaging Mri

Purpose: To investigate the dimensions of the tensor veli palatini (TVP) muscle using high image resolution 3-dimensional magnetic resonance imaging (MRI) of the soft palate among children with normal velopharyngeal and craniofacial anatomy and to compare values to individuals with a diagnosis of 22q11.2 deletion syndrome (22q11DS). We also sought to determine whether there is a relationship between hypoplasia of the TVP and severity of middle ear dysfunction and hearing loss. Methods: Three-dimensional MRI were used to collect and analyze data obtained across 53 children between 4 and 12 years of age, including 40 children with normal velopharyngeal and craniofacial anatomy and 13 children with a diagnosis of 22q11.2 DS. Tensor veli palatini muscle length, thickness, and volume as well as bihamular distance were compared among participant groups. Results: A Welch’s t-test revealed that the TVP in participants with 22q11DS is significantly shorter ( P = .005, 17.3 vs 19.0 mm), thinner ( P < .001, 1.1 vs 1.8 mm), and less voluminous ( P < .001, 457.5 vs 667.3 mm3) than participants without 22q11DS. Participants with 22q11DS also had a greater ( P = .006, 27.7 vs 24.7 mm) bihamular distance than participants without 22q11DS. There was an inverse relationship between TVP abnormalities noted above and the severity of audiologic and otologic histories. Conclusion: The TVP muscle is substantially reduced in volume, length, and thickness in children with 22q11DS. These findings serve as preliminary support for the association of patient hearing and otologic severity and TVP dysmorphology.

Effect of X-Ray µCT Scanning on the Growth and Activity of Microorganisms in a Heap Bioleaching System

2017 ◽  
Vol 262 ◽  
pp. 143-146
Author(s):  
Mehdi Ghadiri ◽  
Susan T.L. Harrison ◽  
Marijke A. Fagan-Endres
Keyword(s):  
Microbial Activity ◽  
Image Resolution ◽  
Cell Counting ◽  
Reaction Products ◽  
Micro Computed Tomography ◽  
X Ray ◽  
Moderately Thermophilic ◽  
Heap Bioleaching ◽  
High Image Resolution ◽  
Surface Mineral

In heap bioleaching, a process in which microorganisms are required for the regeneration of leach reagents and control of reaction products, inaccessibility of non-surface mineral grains is a key cause of low recovery and long extraction times. High resolution, non-destructive 3D X-ray micro-computed tomography (μCT) is an imaging technique that has been successfully demonstrated for the study of abiotic leaching of non-surface minerals. For this technique to be applied to biotic leaching, it is required that the iron and sulphur oxidizing abilities of the microorganisms are not affected by the irradiation experienced. In the current study, the feasibility of investigating biotic leaching by X-ray μCT is explored by examining the relative energies required to achieve the high image resolution needed for mineral grain mapping while avoiding microbial deactivation. A mixed mesophilic and moderately thermophilic culture in solution was used and exposed to various X-ray energy doses. Direct microscopic cell counting and redox potential were measured to quantify the microbial activity and growth. The results showed that exposure to X-ray does not affect microbial activity at 35-90 kV, 200-280 μA and a distance of 7.2 cm between energy source and sample, however, it has an influence at 120 and 150 kV. This indicates that while X-ray μCT does influence the microbial cultures, it can be used for bioleaching studies at lower energy doses.

scholarly journals Deep Neural Frameworks Improve the Accuracy of General Practitioners in the Classification of Pigmented Skin Lesions

Diagnostics ◽  
2020 ◽  
Vol 10 (11) ◽  
pp. 969
Author(s):  
Maximiliano Lucius ◽  
Jorge De All ◽  
José Antonio De All ◽  
Martín Belvisi ◽  
Luciana Radizza ◽  
...  
Keyword(s):  
General Practitioners ◽  
Skin Lesions ◽  
Image Resolution ◽  
Aggregated Data ◽  
Skin Imaging ◽  
High Image Resolution ◽  
Random Dataset ◽  
Algorithmic Framework ◽  
Diagnosis Accuracy ◽  
Pigmented Skin Lesions

This study evaluated whether deep learning frameworks trained in large datasets can help non-dermatologist physicians improve their accuracy in categorizing the seven most common pigmented skin lesions. Open-source skin images were downloaded from the International Skin Imaging Collaboration (ISIC) archive. Different deep neural networks (DNNs) (n = 8) were trained based on a random dataset constituted of 8015 images. A test set of 2003 images was used to assess the classifiers’ performance at low (300 × 224 RGB) and high (600 × 450 RGB) image resolution and aggregated data (age, sex and lesion localization). We also organized two different contests to compare the DNN performance to that of general practitioners by means of unassisted image observation. Both at low and high image resolution, the DNN framework differentiated dermatological images with appreciable performance. In all cases, the accuracy was improved when adding clinical data to the framework. Finally, the least accurate DNN outperformed general practitioners. The physician’s accuracy was statistically improved when allowed to use the output of this algorithmic framework as guidance. DNNs are proven to be high performers as skin lesion classifiers and can improve general practitioner diagnosis accuracy in a routine clinical scenario.

SEM Equipment Capabilities Evaluated for Sub-Half Micron Semiconductor Applications

1997 ◽  
Author(s):  
J. Cowan ◽  
T. Taylor
Keyword(s):  
Electron Microscopy ◽  
Memory Cell ◽  
Image Resolution ◽  
Evaluation Methodology ◽  
Reasonable Cost ◽  
High Image Resolution ◽  
High Assurance ◽  
Electron Microscopes ◽  
Scanning Electron Microscopes ◽  
Scanning Electron

Abstract Evaluation of Scanning Electron Microscopes (SEMs) was initiated for the purpose of purchasing a SEM that would improve the productivity of scanning electron microscopy during the cycle of analysis and deprocessing of semiconductor devices in a failure analysis lab. In addition to the need for high image resolution at low electron acceleration voltages, an accurate motorized stage is a major evaluation factor. It is necessary for the analyst to drive directly to a known location such as a memory cell with a high assurance that the site of interest was found. There are two main areas of focus in this paper. First, our SEM evaluation methodology will be presented along with the results of our evaluation. Second, the technology associated with motorized stages will be discussed in light of our requirements for a motorized, highly accurate stage. As a byproduct of this evaluation, this paper is presented so as to push the SEM industry to offer a SEM with an accurate stage for subhalfmicron products at reasonable cost.

Oil Palm Tree Detection from High Resolution Drone Image Using Convolutional Neural Network

2019 ◽  
Vol 1 (2) ◽  
pp. 6-9
Author(s):  
Chee Cheong Lee ◽  
See Yee Tan ◽  
Tien Sze Lim ◽  
Voon Chet Koo
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Template Matching ◽  
Window Size ◽  
Ground Truth ◽  
Frequency Domain Analysis ◽  
Image Resolution ◽  
Palm Tree ◽  
Tree Detection ◽  
High Image Resolution

We propose a method to combine several image processing methods with Convolutional Neural Network (CNN) to perform palm tree detection and counting. This paper focuses on drone imaging, which has a high image resolution and is widely deployed in the plantation industry. Analyzing drone images is challenging due to variable drone flying altitudes, resulting in inconsistent tree sizes in images captured. Counting by template matching or fixed sliding window size method often produces an inaccurate count. Instead, our method employs frequency domain analysis to estimate tree size before CNN. The method is evaluated using two images, ranging from a few thousand trees to a few hundred thousand trees per image. We have summarized the accuracy of the proposed method by comparing the results with manually labelled ground truth.

Oil Palm Tree Detection from High Resolution Drone Image Using Convolutional Neural Network

2019 ◽  
Vol 1 (2) ◽  
pp. 6-9
Author(s):  
Chee Cheong Lee ◽  
See Yee Tan ◽  
Tien Sze Lim ◽  
Voon Chet Koo
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Template Matching ◽  
Window Size ◽  
Ground Truth ◽  
Frequency Domain Analysis ◽  
Image Resolution ◽  
Palm Tree ◽  
Tree Detection ◽  
High Image Resolution

We propose a method to combine several image processing methods with Convolutional Neural Network (CNN) to perform palm tree detection and counting. This paper focuses on drone imaging, which has a high image resolution and is widely deployed in the plantation industry. Analyzing drone images is challenging due to variable drone flying altitudes, resulting in inconsistent tree sizes in images captured. Counting by template matching or fixed sliding window size method often produces an inaccurate count. Instead, our method employs frequency domain analysis to estimate tree size before CNN. The method is evaluated using two images, ranging from a few thousand trees to a few hundred thousand trees per image. We have summarized the accuracy of the proposed method by comparing the results with manually labelled ground truth.

scholarly journals Randomized study of digital single-operator cholangioscope compared to fiberoptic single-operator cholangioscope in a novel cholangioscopy bench model

2018 ◽  
Vol 06 (07) ◽  
pp. E851-E856 ◽  
Author(s):  
Raj Shah ◽  
Horst Neuhaus ◽  
Mansour Parsi ◽  
D. Reddy ◽  
Douglas Pleskow
Keyword(s):  
Image Quality ◽  
Randomized Study ◽  
Image Resolution ◽  
Ease Of Use ◽  
Wide Field ◽  
Time To Completion ◽  
Wide Field Of View ◽  
High Image Resolution ◽  
Single Operator ◽  
Superior Image Quality

Abstract Background and study aims Cholangiopancreatoscopy is utilized for diagnosis and therapy of pancreaticobiliary disorders. a fully-disposable, digital, single-operator cholangioscope (DSOC) was developed with high image resolution and wide field-of-view. This bench study compared the new DSOC to the previous semi-disposable, fiber-optic cholangioscope (FSOC) prior to the clinical availability of the DSOC system. Methods Five experts performed one practice run followed by randomized runs comparing DSOC to FSOC in a biliary tract model consisting of three fixed left-intrahepatic tracts (LIHD), and variable common bile duct (CBD) and right-intrahepatic tracts (RIHD) with seven total lesions in multiple configurations. Timed runs aimed to visualize and target each lesion using miniature biopsy forceps. Definitions: visual success, visualizing targets; targeting success, touching target with forceps; complete run, touching seven targets within 20 minutes. Image quality, ease-of-use, and time to completion were recorded. Results Thirty-seven evaluable runs (20 DSOC, 17 FSOC) were completed. DSOC was superior to FSOC in Visual (99 % vs. 67 %, P < 0.001) and targeting success (6.6 vs. 4.5, P = 0.009), proportion of complete runs (13 /20 vs. 0 /17, P < 0.001) and time of run (10.1 min vs. 15.4 min, P < 0.001). For fixed LIHD, DSOC achieved higher targeting success compared to FSOC (2.6 vs. 1.1, P < 0.001) with no difference in RIHD and CBD targets (4.0 vs. 3.4, P = 0.39). Investigators reported superior image quality and ease-of-use with DSOC. Conclusions In this model, DSOC performed superiorly to FSOC in image quality, visualization, and maneuverability. The model could potentially be utilized for training endoscopists less experienced with cholangiopancreatoscopy.

scholarly journals Regional and local land subsidence at the Venice coastland by TerraSAR-X PSI

2015 ◽  
Vol 372 ◽  
pp. 199-205 ◽  
Author(s):  
L. Tosi ◽  
T. Strozzi ◽  
C. Da Lio ◽  
P. Teatini
Keyword(s):  
Land Subsidence ◽  
Regional Scale ◽  
Image Resolution ◽  
Persistent Scatterer Interferometry ◽  
Large Structures ◽  
Persistent Scatterer ◽  
X Band ◽  
High Image Resolution ◽  
Under Construction ◽  
The City

Abstract. Land subsidence occurred at the Venice coastland over the 2008–2011 period has been investigated by Persistent Scatterer Interferometry (PSI) using a stack of 90 TerraSAR-X stripmap images with a 3 m resolution and a 11-day revisiting time. The regular X-band SAR acquisitions over more than three years coupled with the very-high image resolution has significantly improved the monitoring of ground displacements at regional and local scales, e.g., the entire lagoon, especially the historical palaces, the MoSE large structures under construction at the lagoon inlets to disconnect the lagoon from the Adriatic Sea during high tides, and single small structures scattered within the lagoon environments. Our results show that subsidence is characterized by a certain variability at the regional scale with superimposed important local displacements. The movements range from a gentle uplift to subsidence rates of up to 35 mm yr−1. For instance, settlements of 30–35 mm yr−1 have been detected at the three lagoon inlets in correspondence of the MoSE works, and local sinking bowls up to 10 mm yr−1 connected with the construction of new large buildings or restoration works have been measured in the Venice and Chioggia historical centers. Focusing on the city of Venice, the mean subsidence of 1.1 ± 1.0 mm yr−1 confirms the general stability of the historical center.

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