Abstract: This disclosure relates to a medical image viewer for incorporating multi-user collaboration features, such as in-image commenting and workspace sharing. An example method includes receiving a comment location including image coordinates and comment information associated with the comment from a user device. The comment information includes a text body, identify identity information related to the user, and a comment creation date. The example method further includes determining world coordinates based on the image coordinates, and storing the world coordinates and the comment information as a subset of header attributes of the DICOM image file.

Abstract: Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) are commonly used to assess patients with known or suspected pathologies of the lungs and liver. In particular, identification and quantification of possibly malignant regions identified in these high-resolution images is essential for accurate and timely diagnosis. However, careful quantitative assessment of lung and liver lesions is tedious and time consuming. This disclosure describes an automated end-to-end pipeline for accurate lesion detection and segmentation.

Abstract: Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) are commonly used to assess patients with known or suspected pathologies of the lungs and liver. In particular, identification and quantification of possibly malignant regions identified in these high-resolution images is essential for accurate and timely diagnosis. However, careful quantitative assessment of lung and liver lesions is tedious and time consuming. This disclosure describes an automated end-to-end pipeline for accurate lesion detection and segmentation.

Abstract: This disclosure relates to a medical image viewer for incorporating multi-user collaboration features, such as in-image commenting and workspace sharing. An example method includes receiving a comment location including image coordinates and comment information associated with the comment from a user device. The comment information includes a text body, identify identity information related to the user, and a comment creation date. The example method further includes determining world coordinates based on the image coordinates, and storing the world coordinates and the comment information as a subset of header attributes of the DICOM image file.

Abstract: Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) are commonly used to assess patients with known or suspected pathologies of the lungs and liver. In particular, identification and quantification of possibly malignant regions identified in these high-resolution images is essential for accurate and timely diagnosis. However, careful quantitative assessment of lung and liver lesions is tedious and time consuming. This disclosure describes an automated end-to-end pipeline for accurate lesion detection and segmentation.