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eess.IV2024
Towards Efficient and Accurate CT Segmentation via Edge-Preserving Probabilistic Downsampling
Shahzad Ali, Yu Rim Lee, Soo Young Park +2
Downsampling images and labels, often necessitated by limited resources or to expedite network training, leads to the loss of small objects and thin boundaries. This undermines the…
eess.IV2020★ 86 cited
Deep Metric Learning-based Image Retrieval System for Chest Radiograph and its Clinical Applications in COVID-19
Aoxiao Zhong, Xiang Li, Dufan Wu +17
In recent years, deep learning-based image analysis methods have been widely applied in computer-aided detection, diagnosis and prognosis, and has shown its value during the public…
eess.IV2020★ 1 cited
Deep Learning-based Four-region Lung Segmentation in Chest Radiography for COVID-19 Diagnosis
Young-Gon Kim, Kyungsang Kim, Dufan Wu +10
Purpose. Imaging plays an important role in assessing severity of COVID 19 pneumonia. However, semantic interpretation of chest radiography (CXR) findings does not include quantita…