Medical Image Computing and Computer Assisted Intervention - MICCAI 2020 - 23rd International Conference, Lima, Peru, October 4-8, 2020, Proceedings, Part VII
Medical Image Computing and Computer Assisted Intervention - MICCAI 2020 - 23rd International Conference, Lima, Peru, October 4-8, 2020, Proceedings, Part VII
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医学图像计算和计算机辅助干预 - MICCAI 2020 - 第 23 届国际会议，秘鲁利马，2020 年 10 月 4-8 日，会议记录，第七部分
DOI：
10.1007/978-3-030-59728-3_33
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发表时间：
2020
期刊：
影响因子：
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通讯作者：
Gasimova A
中科院分区：
文献类型：
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作者：
Gasimova A
根据最近探索自动病理诊断的工作，研究还表明，可以生成具有不同功效水平的医学文本报告。脑弥散加权磁共振成像（DWI）已被用于诊断脑缺血，脑死亡可以在几个小时内立即跟进。因此，在临床环境中尽快获得缺血性脑诊断至关重要。以前的研究表明，可以使用可变密度笛卡尔欠采样方法加速MRI采集。在这项研究中，我们提出了一个加速DWI采集管道的目的是生成包含诊断信息的文本报告。我们证明，我们可以学习一个语义保留的潜在空间，以及极欠采样的MR图像能够实现有希望的结果上的诊断报告生成任务。
In light of recent works exploring automated pathological diagnosis, studies have also shown that medical text reports can be generated with varying levels of efficacy. Brain diffusion-weighted MRI (DWI) has been used for the diagnosis of ischaemia in which brain death can follow in immediate hours. It is therefore of the utmost importance to obtain ischaemic brain diagnosis as soon as possible in a clinical setting. Previous studies have shown that MRI acquisition can be accelerated using variable-density Cartesian undersampling methods. In this study, we propose an accelerated DWI acquisition pipeline for the purpose of generating text reports containing diagnostic information. We demonstrate that we can learn a semantic-preserving latent space for minor as well as extremely undersampled MR images capable of achieving promising results on a diagnostic report generation task.