Search Results - "Thambawita, Vajira"

On evaluation metrics for medical applications of artificial intelligence by Hicks, Steven A., Strümke, Inga, Thambawita, Vajira, Hammou, Malek, Riegler, Michael A., Halvorsen, Pål, Parasa, Sravanthi

“…Clinicians and software developers need to understand how proposed machine learning (ML) models could improve patient care. No single metric captures all the…”
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SinGAN-Seg: Synthetic training data generation for medical image segmentation by Thambawita, Vajira, Salehi, Pegah, Sheshkal, Sajad Amouei, Hicks, Steven A, Hammer, Hugo L, Parasa, Sravanthi, Lange, Thomas de, Halvorsen, Pål, Riegler, Michael A

“…Analyzing medical data to find abnormalities is a time-consuming and costly task, particularly for rare abnormalities, requiring tremendous efforts from…”
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HyperKvasir, a comprehensive multi-class image and video dataset for gastrointestinal endoscopy by Borgli, Hanna, Thambawita, Vajira, Smedsrud, Pia H., Hicks, Steven, Jha, Debesh, Eskeland, Sigrun L., Randel, Kristin Ranheim, Pogorelov, Konstantin, Lux, Mathias, Nguyen, Duc Tien Dang, Johansen, Dag, Griwodz, Carsten, Stensland, Håkon K., Garcia-Ceja, Enrique, Schmidt, Peter T., Hammer, Hugo L., Riegler, Michael A., Halvorsen, Pål, de Lange, Thomas

“…Artificial intelligence is currently a hot topic in medicine. However, medical data is often sparse and hard to obtain due to legal restrictions and lack of…”
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DeepFake electrocardiograms using generative adversarial networks are the beginning of the end for privacy issues in medicine by Thambawita, Vajira, Isaksen, Jonas L., Hicks, Steven A., Ghouse, Jonas, Ahlberg, Gustav, Linneberg, Allan, Grarup, Niels, Ellervik, Christina, Olesen, Morten Salling, Hansen, Torben, Graff, Claus, Holstein-Rathlou, Niels-Henrik, Strümke, Inga, Hammer, Hugo L., Maleckar, Mary M., Halvorsen, Pål, Riegler, Michael A., Kanters, Jørgen K.

“…Recent global developments underscore the prominent role big data have in modern medical science. But privacy issues constitute a prevalent problem for…”
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GridHTM: Grid-Based Hierarchical Temporal Memory for Anomaly Detection in Videos by Monakhov, Vladimir, Thambawita, Vajira, Halvorsen, Pål, Riegler, Michael A

“…The interest in video anomaly detection systems that can detect different types of anomalies, such as violent behaviours in surveillance videos, has gained…”
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Explaining deep neural networks for knowledge discovery in electrocardiogram analysis by Hicks, Steven A., Isaksen, Jonas L., Thambawita, Vajira, Ghouse, Jonas, Ahlberg, Gustav, Linneberg, Allan, Grarup, Niels, Strümke, Inga, Ellervik, Christina, Olesen, Morten Salling, Hansen, Torben, Graff, Claus, Holstein-Rathlou, Niels-Henrik, Halvorsen, Pål, Maleckar, Mary M., Riegler, Michael A., Kanters, Jørgen K.

“…Deep learning-based tools may annotate and interpret medical data more quickly, consistently, and accurately than medical doctors. However, as medical doctors…”
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Impact of Image Resolution on Deep Learning Performance in Endoscopy Image Classification: An Experimental Study Using a Large Dataset of Endoscopic Images by Thambawita, Vajira, Strümke, Inga, Hicks, Steven A, Halvorsen, Pål, Parasa, Sravanthi, Riegler, Michael A

“…Recent trials have evaluated the efficacy of deep convolutional neural network (CNN)-based AI systems to improve lesion detection and characterization in…”
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CELLULAR, A Cell Autophagy Imaging Dataset by Al Outa, Amani, Hicks, Steven, Thambawita, Vajira, Andresen, Siri, Enserink, Jorrit M., Halvorsen, Pål, Riegler, Michael A., Knævelsrud, Helene

“…Cells in living organisms are dynamic compartments that continuously respond to changes in their environment to maintain physiological homeostasis. While basal…”
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A comprehensive analysis of classification methods in gastrointestinal endoscopy imaging by Jha, Debesh, Ali, Sharib, Hicks, Steven, Thambawita, Vajira, Borgli, Hanna, Smedsrud, Pia H., de Lange, Thomas, Pogorelov, Konstantin, Wang, Xiaowei, Harzig, Philipp, Tran, Minh-Triet, Meng, Wenhua, Hoang, Trung-Hieu, Dias, Danielle, Ko, Tobey H., Agrawal, Taruna, Ostroukhova, Olga, Khan, Zeshan, Atif Tahir, Muhammad, Liu, Yang, Chang, Yuan, Kirkerød, Mathias, Johansen, Dag, Lux, Mathias, Johansen, Håvard D., Riegler, Michael A., Halvorsen, Pål

“…•Benchmark of computer vision methods for multi-class gastroendoscopy image classification.•Longitudinal analysis for three consecutive years (2017 till 2019)…”
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Assessing generalisability of deep learning-based polyp detection and segmentation methods through a computer vision challenge by Ali, Sharib, Ghatwary, Noha, Jha, Debesh, Isik-Polat, Ece, Polat, Gorkem, Yang, Chen, Li, Wuyang, Galdran, Adrian, Ballester, Miguel-Ángel González, Thambawita, Vajira, Hicks, Steven, Poudel, Sahadev, Lee, Sang-Woong, Jin, Ziyi, Gan, Tianyuan, Yu, ChengHui, Yan, JiangPeng, Yeo, Doyeob, Lee, Hyunseok, Tomar, Nikhil Kumar, Haithami, Mahmood, Ahmed, Amr, Riegler, Michael A., Daul, Christian, Halvorsen, Pål, Rittscher, Jens, Salem, Osama E., Lamarque, Dominique, Cannizzaro, Renato, Realdon, Stefano, de Lange, Thomas, East, James E.

“…Polyps are well-known cancer precursors identified by colonoscopy. However, variability in their size, appearance, and location makes the detection of polyps…”
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Validating polyp and instrument segmentation methods in colonoscopy through Medico 2020 and MedAI 2021 Challenges by Jha, Debesh, Sharma, Vanshali, Banik, Debapriya, Bhattacharya, Debayan, Roy, Kaushiki, Hicks, Steven A., Tomar, Nikhil Kumar, Thambawita, Vajira, Krenzer, Adrian, Ji, Ge-Peng, Poudel, Sahadev, Batchkala, George, Alam, Saruar, Ahmed, Awadelrahman M.A., Trinh, Quoc-Huy, Khan, Zeshan, Nguyen, Tien-Phat, Shrestha, Shruti, Nathan, Sabari, Gwak, Jeonghwan, Jha, Ritika K., Zhang, Zheyuan, Schlaefer, Alexander, Bhattacharjee, Debotosh, Bhuyan, M.K., Das, Pradip K., Fan, Deng-Ping, Parasa, Sravanthi, Ali, Sharib, Riegler, Michael A., Halvorsen, Pål, de Lange, Thomas, Bagci, Ulas

“…Automatic analysis of colonoscopy images has been an active field of research motivated by the importance of early detection of precancerous polyps. However,…”
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An Open-Access Dataset of Hospitalized Cardiac-Arrest Patients: Machine-Learning-Based Predictions Using Clinical Documentation by Rajapaksha, Lahiru Theekshana Weerasinghe, Vidanagamachchi, Sugandima Mihirani, Gunawardena, Sampath, Thambawita, Vajira

“…Cardiac arrest is a sudden loss of heart function with serious consequences. In developing countries, healthcare professionals use clinical documentation to…”
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Usefulness of Heat Map Explanations for Deep-Learning-Based Electrocardiogram Analysis by Storås, Andrea M, Andersen, Ole Emil, Lockhart, Sam, Thielemann, Roman, Gnesin, Filip, Thambawita, Vajira, Hicks, Steven A, Kanters, Jørgen K, Strümke, Inga, Halvorsen, Pål, Riegler, Michael A

“…Deep neural networks are complex machine learning models that have shown promising results in analyzing high-dimensional data such as those collected from…”
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VISEM-Tracking, a human spermatozoa tracking dataset by Thambawita, Vajira, Hicks, Steven A., Storås, Andrea M., Nguyen, Thu, Andersen, Jorunn M., Witczak, Oliwia, Haugen, Trine B., Hammer, Hugo L., Halvorsen, Pål, Riegler, Michael A.

“…A manual assessment of sperm motility requires microscopy observation, which is challenging due to the fast-moving spermatozoa in the field of view. To obtain…”
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Synthesizing a Talking Child Avatar to Train Interviewers Working with Maltreated Children by Salehi, Pegah, Hassan, Syed Zohaib, Lammerse, Myrthe, Sabet, Saeed Shafiee, Riiser, Ingvild, Røed, Ragnhild Klingenberg, Johnson, Miriam S., Thambawita, Vajira, Hicks, Steven A., Powell, Martine, Lamb, Michael E., Baugerud, Gunn Astrid, Halvorsen, Pål, Riegler, Michael A.

“…When responding to allegations of child sexual, physical, and psychological abuse, Child Protection Service (CPS) workers and police personnel need to elicit…”
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Automated Event Detection and Classification in Soccer: The Potential of Using Multiple Modalities by Nergård Rongved, Olav Andre, Stige, Markus, Hicks, Steven Alexander, Thambawita, Vajira Lasantha, Midoglu, Cise, Zouganeli, Evi, Johansen, Dag, Riegler, Michael Alexander, Halvorsen, Pål

“…Detecting events in videos is a complex task, and many different approaches, aimed at a large variety of use-cases, have been proposed in the literature. Most…”
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AI-Based Video Clipping of Soccer Events by Valand, Joakim Olav, Kadragic, Haris, Hicks, Steven Alexander, Thambawita, Vajira Lasantha, Midoglu, Cise, Kupka, Tomas, Johansen, Dag, Riegler, Michael Alexander, Halvorsen, Pål

“…The current gold standard for extracting highlight clips from soccer games is the use of manual annotations and clippings, where human operators define the…”
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Real-Time Detection of Events in Soccer Videos using 3D Convolutional Neural Networks by Norgard Rongved, Olav A., Hicks, Steven A., Thambawita, Vajira, Stensland, Hakon K., Zouganeli, Evi, Johansen, Dag, Riegler, Michael A., Halvorsen, Pal

“…In this paper, we present an algorithm for automatically detecting events in soccer videos using 3D convolutional neural networks. The algorithm uses a sliding…”
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GridHTM: Grid-Based Hierarchical Temporal Memory for Anomaly Detection in Videos by Monakhov, Vladimir, Thambawita, Vajira L B, Halvorsen, Pål, Riegler, Michael

“…The interest in video anomaly detection systems that can detect different types of anomalies, such as violent behaviours in surveillance videos, has gained…”
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Fr615 IMPACT OF IMAGE RESOLUTION ON CONVOLUTIONAL NEURAL NETWORKS PERFORMANCE IN GASTROINTESTINAL ENDOSCOPY by Thambawita, Vajira L., Hicks, Steven, Strümke, Inga, Riegler, Michael A., Halvorsen, Pal, Parasa, Sravanthi

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