paper-with-me

Papers

COVIDx CT-3: A Large-scale, Multinational, Open-Source Benchmark Dataset for Computer-aided COVID-19 Screening from Chest CT Images

2022-06-07 · Hayden Gunraj, Tia Tuinstra, Alexander Wong

Computed tomography (CT) has been widely explored as a COVID-19 screening and assessment tool to complement RT-PCR testing. To assist radiologists with CT-based COVID-19 screening, a number of computer-aided systems have been proposed. However, many proposed systems are built using CT data which is limited in both quantity and diversity. Motivated to support efforts in the development of machine learning-driven screening systems, we introduce COVIDx CT-3, a large-scale multinational benchmark dataset for detection of COVID-19 cases from chest CT images. COVIDx CT-3 includes 431,205 CT slices from 6,068 patients across at least 17 countries, which to the best of our knowledge represents the largest, most diverse dataset of COVID-19 CT images in open-access form. Additionally, we examine the data diversity and potential biases of the COVIDx CT-3 dataset, finding that significant geographic and class imbalances remain despite efforts to curate data from a wide variety of sources.

📄 PDF Abstract BibTeX arXiv:2206.03043

Code (1)

haydengunraj/COVIDNet-CT tf

Tasks

Computed Tomography (CT)Diversity

Similar Papers 제목 키워드 기반

COVIDx CXR-3: A Large-Scale, Open-Source Benchmark Dataset of Chest X-ray Images for Computer-Aided COVID-19 Diagnostics

2022-06-08 · Maya Pavlova, Tia Tuinstra, Hossein Aboutalebi, Andy Zhao 외

After more than two years since the beginning of the COVID-19 pandemic, the pressure of this crisis continues to devastate globally. The use of chest X-ray (CXR) imaging as a complementary screening strategy to RT-PCR te…

COVIDx CXR-4: An Expanded Multi-Institutional Open-Source Benchmark Dataset for Chest X-ray Image-Based Computer-Aided COVID-19 Diagnostics

2023-11-29 · Yifan Wu, Hayden Gunraj, Chi-en Amy Tai, Alexander Wong

The global ramifications of the COVID-19 pandemic remain significant, exerting persistent pressure on nations even three years after its initial outbreak. Deep learning models have shown promise in improving COVID-19 dia…

Diversity

COVIDx-US -- An open-access benchmark dataset of ultrasound imaging data for AI-driven COVID-19 analytics

2021-03-18 · Ashkan Ebadi, Pengcheng Xi, Alexander MacLean, Stéphane Tremblay 외

The COVID-19 pandemic continues to have a devastating effect on the health and well-being of the global population. Apart from the global health crises, the pandemic has also caused significant economic and financial dif…

Prognosis

COVID-Net: A Tailored Deep Convolutional Neural Network Design for Detection of COVID-19 Cases from Chest X-Ray Images

2020-03-22 · Linda Wang, Alexander Wong

The COVID-19 pandemic continues to have a devastating effect on the health and well-being of the global population. A critical step in the fight against COVID-19 is effective screening of infected patients, with one of t…

COVID-19 Diagnosis

Deepparse : An Extendable, and Fine-Tunable State-Of-The-Art Library for Parsing Multinational Street Addresses

2023-11-20 · David Beauchemin, Marouane Yassine

Segmenting an address into meaningful components, also known as address parsing, is an essential step in many applications from record linkage to geocoding and package delivery. Consequently, a lot of work has been dedic…