An FPGA based Stereoptic Image Capture System

2012 ◽  
Author(s):  
N.E. Murphy ◽  
F. Morgan ◽  
J. Manning
Keyword(s):  
Image Capture

Correlative video enhanced differential interference contrast light microscopy (VDIC)-LM), low-voltage high-resolution SEM (LV-HR-SEM), and high-voltage electron microscopy (HVEM) in the observation of gold-labelled surface antigens and the subjacent cytoskeletal matrix

1989 ◽  
Vol 47 ◽  
pp. 904-905
Author(s):  
Ralph M. Albrecht ◽  
Scott R. Simmons ◽  
Marek Malecki
Keyword(s):  
High Resolution ◽  
Light Microscopy ◽  
Low Voltage ◽  
Microscopic Analysis ◽  
Cell Labelling ◽  
Video Technology ◽  
Electron Microscopic ◽  
Image Capture ◽  
High Voltage Electron Microscopy ◽  
Fluorescence Studies

The development of video-enhanced light microscopy (LM) as well as associated image processing and analysis have significantly broadened the scope of investigations which can be undertaken using (LM). Interference/polarization based microscopies can provide high resolution and higher levels of “detectability” especially in unstained living systems. Confocal light microscopy also holds the promise of further improvements in resolution, fluorescence studies, and 3 dimensional reconstruction. Video technology now provides, among other things, a means to detect differences in contrast difficult to detect with the human eye; furthermore, computerized image capture, processing, and analysis can be used to enhance features of interest, average images, subtract background, and provide a quantitative basis to studies of cells, cell features, cell labelling, and so forth. Improvements in video technology, image capture, and cost-effective computer image analysis/processing have contributed to the utility and potential of the various interference and confocal microscopic instrumentation.Electron microscopic technology has made advances as well. Microprocessor control and improved design have contributed to high resolution SEMs which have imaging capability at the molecular level and can operate at a range of accelerating voltages starting at 1KV. Improvements have also been seen in the HVEM and IVEM transmission instruments. As a whole, these advances in LM and EM microscopic technology provide the biologist with an array of information on structure, composition, and function which can be obtained from a single specimen. Corrrelative light microscopic analysis permits examination of living specimens and is critical where the “history” of a cell, cellular components, or labels needs to be known up to the time of chemical or physical fixation. Features such as cytoskeletal elements or gold label as small as 0.01 μm, well below the 0.2 μm limits of LM resolution, can be “detected” and their movement followed by VDIC-LM. Appropriate identification and preparation can then lead to the examination of surface detail and surface label with stereo LV-HR-SEM. Increasing the KV in the HR-SEM while viewing uncoated or thinly coated specimens can provide information from beneath the surface as well as increasing Z contrast so that positive identification of surface and subsurface colloidal gold or other heavy metal labelled/stained material is possible. Further examination of the same cells using stereo HVEM or IVEM provides information on internal ultrastructure and on the relationship of labelled material to cytoskeletal or organellar distribution, A wide variety of investigations can benefit from this correlative approach and a number of instrumentational configurations and preparative pathways can be tailored for the particular study. For a surprisingly small investment in time and technique, it is often possible to clear ambiguities or questions that arise when a finding is presented in the context of only one modality.

Unique views on obesity-related behaviors and environments: research using still and video images (Preprint)

2018 ◽  
Author(s):  
Jordan Carlson ◽  
J. Aaron Hipp ◽  
Jacqueline Kerr ◽  
Todd Horowitz ◽  
David Berrigan
Keyword(s):  
Physical Activity ◽  
Ethical Issues ◽  
Data Extraction ◽  
Dietary Assessment ◽  
Extraction Methods ◽  
Image Capture ◽  
Still Images ◽  
Key Informants ◽  
Technological Advances ◽  
Computer Scientists

BACKGROUND Image based data collection for obesity research is in its infancy. OBJECTIVE The present study aimed to document challenges to and benefits from such research by capturing examples of research involving the use of images to assess physical activity- or nutrition-related behaviors and/or environments. METHODS Researchers (i.e., key informants) using image capture in their research were identified through knowledge and networks of the authors of this paper and through literature search. Twenty-nine key informants completed a survey covering the type of research, source of images, and challenges and benefits experienced, developed specifically for this study. RESULTS Most respondents used still images in their research, with only 26.7% using video. Image sources were categorized as participant generated (N = 13; e.g., participants using smartphones for dietary assessment), researcher generated (N = 10; e.g., wearable cameras with automatic image capture), or curated from third parties (N = 7; e.g., Google Street View). Two of the major challenges that emerged included the need for automated processing of large datasets (58.8%) and participant recruitment/compliance (41.2%). Benefit-related themes included greater perspectives on obesity with increased data coverage (34.6%) and improved accuracy of behavior and environment assessment (34.6%). CONCLUSIONS Technological advances will support the increased use of images in the assessment of physical activity, nutrition behaviors, and environments. To advance this area of research, more effective collaborations are needed between health and computer scientists. In particular development of automated data extraction methods for diverse aspects of behavior, environment, and food characteristics are needed. Additionally, progress in standards for addressing ethical issues related to image capture for research purposes are critical. CLINICALTRIAL NA

A Novel Thyroid Ultrasound Proficiency Metric Designed Through a Multidisciplinary Delphi Approach

2021 ◽  
pp. 000313482110111
Author(s):  
Yinin Hu ◽  
Alex D. Michaels ◽  
Rachita Khot ◽  
Worthington G. Schenk ◽  
John B. Hanks ◽  
...  
Keyword(s):  
Learning Curves ◽  
Delphi Panel ◽  
Thyroid Ultrasound ◽  
Point Scale ◽  
Image Capture ◽  
Delphi Approach ◽  
Inflection Points ◽  
Operative Planning ◽  
Positioning Technique ◽  
Formally Trained

Background Thyroid ultrasounds extend surgeons’ outpatient capabilities and are essential for operative planning. However, most residents are not formally trained in thyroid ultrasound. The purpose of this study was to create a novel thyroid ultrasound proficiency metric through a collaborative Delphi approach. Methods Clinical faculty experienced in thyroid ultrasound participated on a Delphi panel to design the thyroid Ultrasound Proficiency Scale (UPS-Thyroid). Participants proposed items under the categories of Positioning, Technique, Image Capture, Measurement, and Interpretation. In subsequent rounds, participants voted to retain, revise, or exclude each item. The process continued until all items had greater than 70% consensus for retention. The UPS-Thyroid was pilot tested across 5 surgery residents with moderate ultrasound experience. Learning curves were assessed with cumulative sum. Results Three surgeons and 4 radiologists participated on the Delphi panel. Following 3 iterative Delphi rounds, the panel arrived at >70% consensus to retain 14 items without further revisions or additions. The metric included the following items on a 3-point scale for a maximum of 42 points: Positioning (1 item), Technique (4 items), Image Capture (2 items), Measurement (2 items), and Interpretation (5 items). A pilot group of 5 residents was scored against a proficiency threshold of 36 points. Learning curve inflection points were noted at between 4 to 7 repetitions. Conclusions A multidisciplinary Delphi approach generated consensus for a thyroid ultrasound proficiency metric (UPS-Thyroid). Among surgery residents with moderate ultrasound experience, basic proficiency at thyroid ultrasound is feasible within 10 repetitions.

scholarly journals Amalgamation of cloud-based colonoscopy videos with patient-level metadata to facilitate large-scale machine learning

2021 ◽  
Vol 09 (02) ◽  
pp. E233-E238
Author(s):  
Rajesh N. Keswani ◽  
Daniel Byrd ◽  
Florencia Garcia Vicente ◽  
J. Alex Heller ◽  
Matthew Klug ◽  
...  
Keyword(s):  
Machine Learning ◽  
Large Scale ◽  
Medical Center ◽  
Academic Medical Center ◽  
Procedure Time ◽  
Image Capture ◽  
Common Procedure ◽  
Patient Level Data ◽  
Patient Level ◽  
Level Data

Abstract Background and study aims Storage of full-length endoscopic procedures is becoming increasingly popular. To facilitate large-scale machine learning (ML) focused on clinical outcomes, these videos must be merged with the patient-level data in the electronic health record (EHR). Our aim was to present a method of accurately linking patient-level EHR data with cloud stored colonoscopy videos. Methods This study was conducted at a single academic medical center. Most procedure videos are automatically uploaded to the cloud server but are identified only by procedure time and procedure room. We developed and then tested an algorithm to match recorded videos with corresponding exams in the EHR based upon procedure time and room and subsequently extract frames of interest. Results Among 28,611 total colonoscopies performed over the study period, 21,170 colonoscopy videos in 20,420 unique patients (54.2 % male, median age 58) were matched to EHR data. Of 100 randomly sampled videos, appropriate matching was manually confirmed in all. In total, these videos represented 489,721 minutes of colonoscopy performed by 50 endoscopists (median 214 colonoscopies per endoscopist). The most common procedure indications were polyp screening (47.3 %), surveillance (28.9 %) and inflammatory bowel disease (9.4 %). From these videos, we extracted procedure highlights (identified by image capture; mean 8.5 per colonoscopy) and surrounding frames. Conclusions We report the successful merging of a large database of endoscopy videos stored with limited identifiers to rich patient-level data in a highly accurate manner. This technique facilitates the development of ML algorithms based upon relevant patient outcomes.

scholarly journals Image capture device based on Internet of Thing (IoT ) technology

2021 ◽  
Vol 1088 (1) ◽  
pp. 012065
Author(s):  
Khairul Imtihan ◽  
Wire Bagye ◽  
Zaen Mohammad Taufan Asri ◽  
Sofiansyah Fadli ◽  
Maulana Ashari
Keyword(s):  
Image Capture ◽  
Internet Of Thing

scholarly journals A Pixel Design of a Branching Ultra-Highspeed Image Sensor

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2506
Author(s):  
Nguyen Hoai Ngo ◽  
Kazuhiro Shimonomura ◽  
Taeko Ando ◽  
Takayoshi Shimura ◽  
Heiji Watanabe ◽  
...  
Keyword(s):  
Image Sensor ◽  
Frame Rate ◽  
Front Side ◽  
Digital Signals ◽  
Memory Element ◽  
Image Capture ◽  
Readout Circuits ◽  
Pros And Cons ◽  
Very High

A burst image sensor named Hanabi, meaning fireworks in Japanese, includes a branching CCD and multiple CMOS readout circuits. The sensor is backside-illuminated with a light/charge guide pipe to minimize the temporal resolution by suppressing the horizontal motion of signal carriers. On the front side, the pixel has a guide gate at the center, branching to six first-branching gates, each bifurcating to second-branching gates, and finally connected to 12 (=6×2) floating diffusions. The signals are either read out after an image capture operation to replay 12 to 48 consecutive images, or continuously transferred to a memory chip stacked on the front side of the sensor chip and converted to digital signals. A CCD burst image sensor enables a noiseless signal transfer from a photodiode to the in-situ storage even at very high frame rates. However, the pixel count conflicts with the frame count due to the large pixel size for the relatively large in-pixel CCD memory elements. A CMOS burst image sensor can use small trench-type capacitors for memory elements, instead of CCD channels. However, the transfer noise from a floating diffusion to the memory element increases in proportion to the square root of the frame rate. The Hanabi chip overcomes the compromise between these pros and cons.

Active learning for road lane landmark inventory with V-ELM in highly uncontrolled image capture conditions

2021 ◽  
Vol 438 ◽  
pp. 259-269
Author(s):  
Jose Manuel Lopez-Guede ◽  
Asier Izquierdo ◽  
Julian Estevez ◽  
Manuel Graña
Keyword(s):  
Active Learning ◽  
Image Capture
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