Automatic segmentation of hepatic metastases on dwi images based on a deep learning method: assessment of tumor treatment response according to the recist 1.1 criteria

HIGHLIGHTS

SUMMARY

About 5% of newly diagnosed cancer patients presented with synchronous liver metastases and the presence of liver metastasis was associated with reduced survival. Image-based evaluation, using either computed tomography (CT) or magnetic_resonance imaging (MRI) images, can noninvasively visualize the tumor during the treatment. Compared with CT, liver magnetic_resonance imaging (MRI) is superior for hepatic metastasis evaluation. The authors proposed a deep learning-based liver metastases segmentation method to assess the treatment response on DWI images according to the RECIST1.1 criteria. The initial cohort (2017.1-2020.12) was used to develop the . . .

 



If you want to have access to all the content you need to log in!

Thanks :)

Username or Email

Password

Remember me

Lost your password?

If you don't have an account, you can create one here.