2024
DOI: 10.47392/irjaeh.2024.0141
|View full text |Cite
|
Sign up to set email alerts
|

Automated Liver Tumor Segmentation in DCE-MRI with 4D Deep Learning Integrating 3D CNNS and ConvLSTM

Sriram,
Karthik

Abstract: A state-of-the-art method for automatically segmenting liver tumours using Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) is shown in this study. This study is significant because it uses a 4D information deep learning model to tackle the hard problem of liver tumor segmentation. A combination of 3D CNNs and ConvLSTM networks, specifically built to capture spatial and temporal information inside the dynamic imaging sequence of DCE-MRI, is what the suggested model is all about. Utilizing diffusi… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

0
0
0

Publication Types

Select...

Relationship

0
0

Authors

Journals

citations
Cited by 0 publications
references
References 12 publications
0
0
0
Order By: Relevance

No citations

Set email alert for when this publication receives citations?