scholarly journals EyeKeys: A Real-Time Vision Interface Based on Gaze Detection from a Low-Grade Video Camera

2005 ◽  
Author(s):  
J.J. Magee ◽  
M.R. Scott ◽  
B.N. Waber ◽  
M. Betke
Keyword(s):  
Real Time ◽  
Video Camera ◽  
Low Grade ◽  
Gaze Detection

scholarly journals Clinical Utility of Real-Time Targeted Molecular Profiling in the Clinical Management of Ovarian Cancer: The ALLOCATE Study

2019 ◽  
pp. 1-18
Author(s):  
Olga Kondrashova ◽  
Gwo-Yaw Ho ◽  
George Au-Yeung ◽  
Leakhena Leas ◽  
Tiffany Boughtwood ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Real Time ◽  
Targeted Therapies ◽  
Clinical Management ◽  
Clinical Utility ◽  
Advanced Ovarian Cancer ◽  
Molecular Profiling ◽  
Molecular Testing ◽  
Low Grade ◽  
Ovarian Carcinomas

PURPOSE The ALLOCATE study was designed as a pilot to demonstrate the feasibility and clinical utility of real-time targeted molecular profiling of patients with recurrent or advanced ovarian cancer for identification of potential targeted therapies. PATIENTS AND METHODS A total of 113 patients with ovarian cancer of varying histologies were recruited from two tertiary hospitals, with 99 patient cases suitable for prospective analysis. Targeted molecular and methylation profiling of fresh biopsy and archived tumor samples were performed by screening for mutations or copy-number variations in 44 genes and for promoter methylation of BRCA1 and RAD51C. RESULTS Somatic genomic or methylation events were identified in 85% of all patient cases, with potentially actionable events with defined targeted therapies (including four resistance events) detected in 60% of all patient cases. On the basis of these findings, six patients received molecularly guided therapy, three patients had unsuspected germline cancer–associated BRCA1/ 2 mutations and were referred for genetic counseling, and two intermediate differentiated (grade 2) serous ovarian carcinomas were reclassified as low grade, leading to changes in clinical management. Additionally, secondary reversion mutations in BRCA1/ 2 were identified in fresh biopsy samples of two patients, consistent with clinical platinum/poly (ADP-ribose) polymerase inhibitor resistance. Timely reporting of results if molecular testing is done at disease recurrence, as well as early referral for patients with platinum-resistant cancers, were identified as factors that could improve the clinical utility of molecular profiling. CONCLUSION ALLOCATE molecular profiling identified known genomic and methylation alterations of the different ovarian cancer subtypes and was deemed feasible and useful in routine clinical practice. Better patient selection and access to a wider range of targeted therapies or clinical trials will further enhance the clinical utility of molecular profiling.

Processing Panorama Video in Real-time

2014 ◽  
Vol 08 (02) ◽  
pp. 209-227 ◽  
Author(s):  
Håkon Kvale Stensland ◽  
Vamsidhar Reddy Gaddam ◽  
Marius Tennøe ◽  
Espen Helgedagsrud ◽  
Mikkel Næss ◽  
...  
Keyword(s):  
Real Time ◽  
Graphics Processing Units ◽  
Low Cost ◽  
Video Camera ◽  
Wide Field ◽  
High Data ◽  
Data Rates ◽  
Camera Arrays ◽  
Analysis System ◽  
Performance Results

There are many scenarios where high resolution, wide field of view video is useful. Such panorama video may be generated using camera arrays where the feeds from multiple cameras pointing at different parts of the captured area are stitched together. However, processing the different steps of a panorama video pipeline in real-time is challenging due to the high data rates and the stringent timeliness requirements. In our research, we use panorama video in a sport analysis system called Bagadus. This system is deployed at Alfheim stadium in Tromsø, and due to live usage, the video events must be generated in real-time. In this paper, we describe our real-time panorama system built using a low-cost CCD HD video camera array. We describe how we have implemented different components and evaluated alternatives. The performance results from experiments ran on commodity hardware with and without co-processors like graphics processing units (GPUs) show that the entire pipeline is able to run in real-time.

scholarly journals High-Quality Transmission of Cardiotocogram and Fetal Information Using a 5G System: Pilot Experiment (Preprint)

2020 ◽  
Author(s):  
Katsuhiko Naruse ◽  
Tomoya Yamashita ◽  
Yukari Onishi ◽  
Yuhi Niitaka ◽  
Fumikage Uchida ◽  
...  
Keyword(s):  
Real Time ◽  
Video Camera ◽  
Ultrasound Images ◽  
Radio Waves ◽  
High Definition ◽  
Waveform Data ◽  
High Definition Video ◽  
Other Information ◽  
Emergency Transport ◽  
The Status

BACKGROUND A cardiotocogram (CTG) is a device used to perceive the status of a fetus in utero in real time. There are a few reports of its use at home or during emergency transport. OBJECTIVE The aim of this study was to test whether CTG and other perinatal information can be transmitted accurately using an experimental station with a 5G transmission system. METHODS In the research institute, real-time fetal heart rate waveform data from the CTG device, high-definition video ultrasound images of the fetus, and high-definition video taken with a video camera on a single line were transmitted by 5G radio waves from the transmitting station to the receiving station. RESULTS All data were proven to be transmitted with a minimum delay of less than 1 second. The CTG waveform image quality was not inferior, and there was no interruption in transmission. Images of the transmitted ultrasound examination and video movie were fine and smooth. CONCLUSIONS CTG and other information about the fetuses and pregnant women were successfully transmitted by a 5G system. This finding will lead to prompt and accurate medical treatment and improve the prognosis of newborns.

scholarly journals High-Quality Transmission of Cardiotocogram and Fetal Information Using a 5G System: Pilot Experiment

10.2196/19744 ◽  
2020 ◽  
Vol 8 (9) ◽  
pp. e19744
Author(s):  
Katsuhiko Naruse ◽  
Tomoya Yamashita ◽  
Yukari Onishi ◽  
Yuhi Niitaka ◽  
Fumikage Uchida ◽  
...  
Keyword(s):  
Real Time ◽  
Video Camera ◽  
Ultrasound Images ◽  
Radio Waves ◽  
High Definition ◽  
Waveform Data ◽  
High Definition Video ◽  
Other Information ◽  
Emergency Transport ◽  
The Status

Background A cardiotocogram (CTG) is a device used to perceive the status of a fetus in utero in real time. There are a few reports of its use at home or during emergency transport. Objective The aim of this study was to test whether CTG and other perinatal information can be transmitted accurately using an experimental station with a 5G transmission system. Methods In the research institute, real-time fetal heart rate waveform data from the CTG device, high-definition video ultrasound images of the fetus, and high-definition video taken with a video camera on a single line were transmitted by 5G radio waves from the transmitting station to the receiving station. Results All data were proven to be transmitted with a minimum delay of less than 1 second. The CTG waveform image quality was not inferior, and there was no interruption in transmission. Images of the transmitted ultrasound examination and video movie were fine and smooth. Conclusions CTG and other information about the fetuses and pregnant women were successfully transmitted by a 5G system. This finding will lead to prompt and accurate medical treatment and improve the prognosis of newborns.

scholarly journals Real-Time Color Correction Method for a Low-Cost Still/Video Camera

2009 ◽  
Vol E92-D (1) ◽  
pp. 97-101
Author(s):  
Dongil HAN ◽  
Hak-Sung LEE ◽  
Chan IM ◽  
Seong Joon YOO
Keyword(s):  
Real Time ◽  
Low Cost ◽  
Video Camera ◽  
Correction Method ◽  
Color Correction

scholarly journals Interpretable multimodal deep learning for real-time pan-tissue pan-disease pathology search on social media

2020 ◽  
Vol 33 (11) ◽  
pp. 2169-2185 ◽  
Author(s):  
Andrew J. Schaumberg ◽  
Wendy C. Juarez-Nicanor ◽  
Sarah J. Choudhury ◽  
Laura G. Pastrián ◽  
Bobbi S. Pritt ◽  
...  
Keyword(s):  
Social Media ◽  
Deep Learning ◽  
Patient Care ◽  
Real Time ◽  
Improve Patient Care ◽  
Low Grade ◽  
Search Performance ◽  
Cell Nuclei ◽  
Disease States ◽  
Share Data

Abstract Pathologists are responsible for rapidly providing a diagnosis on critical health issues. Challenging cases benefit from additional opinions of pathologist colleagues. In addition to on-site colleagues, there is an active worldwide community of pathologists on social media for complementary opinions. Such access to pathologists worldwide has the capacity to improve diagnostic accuracy and generate broader consensus on next steps in patient care. From Twitter we curate 13,626 images from 6,351 tweets from 25 pathologists from 13 countries. We supplement the Twitter data with 113,161 images from 1,074,484 PubMed articles. We develop machine learning and deep learning models to (i) accurately identify histopathology stains, (ii) discriminate between tissues, and (iii) differentiate disease states. Area Under Receiver Operating Characteristic (AUROC) is 0.805–0.996 for these tasks. We repurpose the disease classifier to search for similar disease states given an image and clinical covariates. We report precision@k = 1 = 0.7618 ± 0.0018 (chance 0.397 ± 0.004, mean ±stdev ). The classifiers find that texture and tissue are important clinico-visual features of disease. Deep features trained only on natural images (e.g., cats and dogs) substantially improved search performance, while pathology-specific deep features and cell nuclei features further improved search to a lesser extent. We implement a social media bot (@pathobot on Twitter) to use the trained classifiers to aid pathologists in obtaining real-time feedback on challenging cases. If a social media post containing pathology text and images mentions the bot, the bot generates quantitative predictions of disease state (normal/artifact/infection/injury/nontumor, preneoplastic/benign/low-grade-malignant-potential, or malignant) and lists similar cases across social media and PubMed. Our project has become a globally distributed expert system that facilitates pathological diagnosis and brings expertise to underserved regions or hospitals with less expertise in a particular disease. This is the first pan-tissue pan-disease (i.e., from infection to malignancy) method for prediction and search on social media, and the first pathology study prospectively tested in public on social media. We will share data through http://pathobotology.org. We expect our project to cultivate a more connected world of physicians and improve patient care worldwide.

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