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Prior Clinico-Radiological Features Informed Multi-Modal MR Images Convolution Neural Network: A novel deep learning framework for prediction of lymphovascular invasion in breast cancer.

Hong Zheng | Lian Jian | Li Li | Wen Liu | Wei Chen
Cancer medicine | 2024

Current methods utilizing preoperative magnetic resonance imaging (MRI)-based radiomics for assessing lymphovascular invasion (LVI) in patients with early-stage breast cancer lack precision, limiting the options for surgical planning.

Pubmed ID: 38230837

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This is a list of tools and resources that we have found mentioned in this publication.


3D Slicer (tool)

RRID:SCR_005619

A free, open source software package for visualization and image analysis including registration, segmentation, and quantification of medical image data. Slicer provides a graphical user interface to a powerful set of tools so they can be used by end-user clinicians and researchers alike. 3D Slicer is natively designed to be available on multiple platforms, including Windows, Linux and Mac Os X. Slicer is based on VTK (http://public.kitware.com/vtk) and has a modular architecture for easy addition of new functionality. It uses an XML-based file format called MRML - Medical Reality Markup Language which can be used as an interchange format among medical imaging applications. Slicer is primarily written in C++ and Tcl.

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Editage (tool)

RRID:SCR_019209

Web service for all stages of manuscript writing and publication. Offers Translation services where manuscript will be converted to English by translators ,Publication Support services to assist with journal selection and journal submission, manuscript editing.

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