Apr 1, 2020 · In this paper we propose an automatic approach for labeling chest x-ray images for findings and locations by leveraging radiology reports.
This paper proposes an automatic approach for labeling chest x-ray images for findings and locations by leveraging radiology reports.
... An anatomical bounding box (Bbox) extraction pipeline was used to automatically extract the coordinates for the left lung, right lung, mediastinum, and ...
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With this in mind, in this paper we propose an textit{automatic} approach for labeling chest x-ray images for findings and locations by leveraging radiology ...
Apr 7, 2020 · ABSTRACT. Automatic detection of findings and their locations in chest x-ray studies is an important research area for AI application.
We proposed a machine-learning method to generate bounding boxes with disease lesion on chest X ray (CXR) images based on the location of the lesion extracted ...
Sep 18, 2023 · Our research focused on creating an advanced machine-learning algorithm that accurately detects anomalies in chest X-ray images
Jul 20, 2022 · In this work, we describe a dataset of more than 100,000 chest X-ray scans that were retrospectively collected from two major hospitals in ...
Feb 14, 2024 · A deep-learning pipeline for the diagnosis and discrimination of viral, non-viral and COVID-19 pneumonia from chest X-ray images.
Learning to localize or detect objects typically requires the collection of data that has been labelled with bounding boxes or similar annotations, which can be ...