The radiological diagnosis of bronchiectasis: what's in a name?

Diagnosis of bronchiectasis is usually made using chest computed tomography (CT) scan, the current gold standard method. A bronchiectatic airway can show abnormal widening and thickening of its airway wall. In addition, it can show an irregular wall and lack of tapering, and/or can be visible in the periphery of the lung. Its diagnosis is still largely expert based. More recently, it has become clear that airway dimensions on CT and therefore the diagnosis of bronchiectasis are highly dependent on lung volume. Hence, control of lung volume is required during CT acquisition to standardise the evaluation of airways. Automated image analysis systems are in development for the objective analysis of airway dimensions and for the diagnosis of bronchiectasis. To use these systems, clear and objective definitions for the diagnosis of bronchiectasis are needed. Furthermore, the use of these systems requires standardisation of CT protocols and of lung volume during chest CT acquisition. In addition, sex- and age-specific reference values are needed for image analysis outcome parameters. This review focusses on today's issues relating to the radiological diagnosis of bronchiectasis using state-of-the-art CT imaging techniques.

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Effects of lung volume, bronchoconstriction, and cigarette smoke on morphometric airway dimensions

Journal of Applied Physiology ◽

10.1152/jappl.1988.64.3.913 ◽

1988 ◽

Vol 64 (3) ◽

pp. 913-919 ◽

Cited By ~ 26

Author(s):

A. L. James ◽

P. D. Pare ◽

J. C. Hogg

Keyword(s):

Smooth Muscle ◽

Cigarette Smoke ◽

Lung Volume ◽

Muscle Tone ◽

Cigarette Smoke Exposure ◽

Wall Thickening ◽

Airway Wall ◽

Lung Inflation ◽

Wall Area ◽

Airway Dimensions

To examine the role of airway wall thickening in the bronchial hyperresponsiveness observed after exposure to cigarette smoke, we compared the airway dimensions of guinea pigs exposed to smoke (n = 7) or air (n = 7). After exposure the animals were anesthetized with urethan, pulmonary resistance was measured, and the lungs were removed, distended with Formalin, and fixed near functional residual capacity. The effects of lung inflation and bronchoconstriction on airway dimensions were studied separately by distending and fixing lungs with Formalin at total lung capacity (TLC) (n = 3), 50% TLC (n = 3), and 25% TLC (n = 3) or near residual volume after bronchoconstriction (n = 3). On transverse sections of extraparenchymal and intraparenchymal airways the following dimensions were measured: the internal area (Ai) and internal perimeter (Pi), defined by the epithelium, and the external area (Ae) and external perimeter (Pe), defined by the outer border of smooth muscle. Airway wall area (WA) was then calculated, WA = Ae - Ai. Ai, Pe, and Ae decreased with decreasing lung volume and after bronchoconstriction. However, WA and Pi did not change significantly with lung volume or after bronchoconstriction. After cigarette smoke exposure airway resistance was increased (P less than 0.05); however, there was no difference in WA between the smoke- and air-exposed groups when the airways were matched by Pi. We conclude that Pi and WA are constant despite changes in lung volume and smooth muscle tone and that airway hyperresponsiveness induced by cigarette smoke is not mediated by increased airway wall thickness.

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Fine-Aggregate Angularity: Automated Image Analysis Approach

Transportation Research Record Journal of the Transportation Research Board ◽

10.3141/1721-08 ◽

2000 ◽

Vol 1721 (1) ◽

pp. 66-72 ◽

Cited By ~ 23

Author(s):

Eyad Masad ◽

Joe W. Button ◽

Tom Papagiannakis

Keyword(s):

Image Analysis ◽

Visual Analysis ◽

Imaging Techniques ◽

Permanent Deformation ◽

Asphalt Mixtures ◽

Automated Image Analysis ◽

Fine Aggregate ◽

Smoothing Effect ◽

Aggregate Properties ◽

Wide Range

Angularity is one of the important aggregate properties contributing to the permanent deformation resistance of asphalt mixtures. Therefore, methods that are able to rapidly and accurately describe aggregate angularity are valuable in the design process of asphalt mixtures. Two computer-automated procedures, which make use of the advances in digital-image processing, to quantify fine aggregate angularity, are presented. The first method relies on the concepts of the erosion-dilation techniques. This consists of subjecting the aggregate surface to a smoothing effect that causes the angularity elements to disappear from the image. Then, the area lost as a result of the smoothing effect is calculated and used to quantify angularity. The second method is based on the fractal approach. Image-analysis techniques are used to measure the fractal length of aggregate boundary. The fractal length increases with aggregate angularity. The proposed imaging techniques are used to capture the aggregate angularity of 23 sand samples that represent a wide range of materials. The results are compared with visual analysis and indirect methods of measuring fine-aggregate angularity, such as the uncompacted air voids, and the angle of internal friction of aggregate mass. In general, the results indicate much promise for measuring aggregate properties using automated imaging technologies.

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Automation strategies for large-scale 3D image analysis

at - Automatisierungstechnik ◽

10.1515/auto-2016-0019 ◽

2016 ◽

Vol 64 (7) ◽

Cited By ~ 1

Author(s):

Johannes Stegmaier ◽

Benjamin Schott ◽

Eduard Hübner ◽

Manuel Traub ◽

Maryam Shahid ◽

...

Keyword(s):

Image Analysis ◽

Large Scale ◽

Imaging Techniques ◽

Image Data ◽

Automated Image Analysis ◽

Future Research ◽

Time Resolved ◽

Processing Strategies ◽

Spatio Temporal ◽

Automation Strategies

AbstractNew imaging techniques enable visualizing and analyzing a multitude of unknown phenomena in many areas of science at high spatio-temporal resolution. The rapidly growing amount of image data, however, can hardly be analyzed manually and, thus, future research has to focus on automated image analysis methods that allow one to reliably extract the desired information from large-scale multidimensional image data. Starting with infrastructural challenges, we present new software tools, validation benchmarks and processing strategies that help coping with large-scale image data. The presented methods are illustrated on typical problems observed in developmental biology that can be answered, e.g., by using time-resolved 3D microscopy images.

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MIA: An Open Source Standalone Deep Learning Application for Microscopic Image Analysis

10.1101/2022.01.14.476308 ◽

2022 ◽

Author(s):

Nils Koerber

Keyword(s):

Image Analysis ◽

Deep Learning ◽

Open Source ◽

Imaging Techniques ◽

Learning Algorithms ◽

Automated Image Analysis ◽

Image Analyzer ◽

Microscopic Image ◽

Biomedical Sciences ◽

Model Training

In recent years the amount of data generated by imaging techniques has grown rapidly along with increasing computational power and the development of deep learning algorithms. To address the need for powerful automated image analysis tools for a broad range of applications in the biomedical sciences, we present the Microscopic Image Analyzer (MIA). MIA combines a graphical user interface that obviates the need for programming skills with state-of-the-art deep learning algorithms for segmentation, object detection, and classification. It runs as a standalone, platform-independent application and is compatible with commonly used open source software packages. The software provides a unified interface for easy image labeling, model training and inference. Furthermore the software was evaluated in a public competition and performed among the top three for all tested data sets. The source code is available on https://github.com/MIAnalyzer/MIA.

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Automated Image Analysis Of Nuclear And Cytoplasmic Changes In Exfoliated Cells From Tracheas Treated With Carcinogen

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100078638 ◽

1977 ◽

Vol 35 ◽

pp. 220-221

Author(s):

S.F. Stinson ◽

J.C. Lilga ◽

M.B. Sporn

Keyword(s):

Image Analysis ◽

Pattern Analysis ◽

Relative Proportion ◽

Automated Image Analysis ◽

Image Analyzer ◽

Cross Sectional ◽

Exfoliated Cells ◽

Neoplastic Lesions ◽

Analysis System ◽

Morphologic Criterion

Increased nuclear size, resulting in an increase in the relative proportion of nuclear to cytoplasmic sizes, is an important morphologic criterion for the evaluation of neoplastic and pre-neoplastic cells. This paper describes investigations into the suitability of automated image analysis for quantitating changes in nuclear and cytoplasmic cross-sectional areas in exfoliated cells from tracheas treated with carcinogen.Neoplastic and pre-neoplastic lesions were induced in the tracheas of Syrian hamsters with the carcinogen N-methyl-N-nitrosourea. Cytology samples were collected intra-tracheally with a specially designed catheter (1) and stained by a modified Papanicolaou technique. Three cytology specimens were selected from animals with normal tracheas, 3 from animals with dysplastic changes, and 3 from animals with epidermoid carcinoma. One hundred randomly selected cells on each slide were analyzed with a Bausch and Lomb Pattern Analysis System automated image analyzer.

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Progress In The Practical Application Of Automated Image Analysis To Tem Negatives

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100078614 ◽

1977 ◽

Vol 35 ◽

pp. 214-217

Author(s):

F. A. Heckman ◽

E. Redman ◽

J.E. Connolly

Keyword(s):

Image Analysis ◽

Image Quality ◽

Exposure Time ◽

Image Contrast ◽

Automated Image Analysis ◽

Practical Application ◽

Factors Affecting ◽

High Image Quality ◽

Qualitative Evidence ◽

Comprehensive Study

In our initial publication on this subject1) we reported results demonstrating that contrast is the most important factor in producing the high image quality required for reliable image analysis. We also listed the factors which enhance contrast in order of the experimentally determined magnitude of their effect. The two most powerful factors affecting image contrast attainable with sheet film are beam intensity and KV. At that time we had only qualitative evidence for the ranking of enhancing factors. Later we carried out the densitometric measurements which led to the results outlined below.Meaningful evaluations of the cause-effect relationships among the considerable number of variables in preparing EM negatives depend on doing things in a systematic way, varying only one parameter at a time. Unless otherwise noted, we adhered to the following procedure evolved during our comprehensive study:Philips EM-300; 30μ objective aperature; magnification 7000- 12000X, exposure time 1 second, anti-contamination device operating.

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Interfacing of a TEM/STEM System to a Computer

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100097818 ◽

1981 ◽

Vol 39 ◽

pp. 250-251

Author(s):

P. Hagemann

Keyword(s):

Image Analysis ◽

Transmission Rate ◽

Analytical Electron Microscopy ◽

Signal Beam ◽

Automated Image Analysis ◽

Beam Deflection ◽

External Control ◽

Computer Input ◽

Instrument Control ◽

Data Acquisition And Processing

The use of computers in the analytical electron microscopy today shows three different trends (1) automated image analysis with dedicated computer systems, (2) instrument control by microprocessors and (3) data acquisition and processing e.g. X-ray or EEL Spectroscopy.While image analysis in the T.E.M. usually needs a television chain to get a sequential transmission suitable as computer input, the STEM system already has this necessary facility. For the EM400T-STEM system therefore an interface was developed, that allows external control of the beam deflection in TEM as well as the control of the STEM probe and video signal/beam brightness on the STEM screen.The interface sends and receives analogue signals so that the transmission rate is determined by the convertors in the actual computer periphery.

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