Advancement in 3-D Medical Images Using Artificial Intelligence Techniques
This paper presents a comprehensive review of recent advancements in 3D medical imaging utilizing artificial intelligence (AI) techniques. The review encompasses various studies focused on different applications and types of 3D medical imaging modalities. The literature review discusses works such as deep learning models for brain tumor segmentation in MRI data, active learning strategies for COVID-19 infection segmentation in CT scans, multi-class point cloud completion networks for cardiac anatomy reconstruction from cine MRI images and deep CNN for total brain volume estimation from 3D ultrasound images, among others. Additionally, the paper includes a detailed analysis of techniques and outcomes, summarized in a table, providing insights into the efficacy of different AI approaches in medical imaging tasks. Moreover, the applications and types of 3D medical imaging modalities discussed in the reviewed studies span across various domains including oncology and surgery.
Authors
- Vanshika Jain
- Yogesh Kumar
- Khushi Tekwani
Institutions
- Pandit Deendayal Energy University (IN)
Publication Details
- Published
- 2024-09-27
- DOI
- https://doi.org/10.1109/tensymp61132.2024.10752259
- Citations
- 1
- Primary Topic
- Medical Imaging and Analysis
- Type
- article
- Field-Weighted Citation Impact
- 0.18