# Online learning for X-ray, CT or MRI

arXiv: https://arxiv.org/abs/2306.06491 · HTML: https://mlsanity.com/paper/2306.06491/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 4 of its 39 references that are in the map.
- First posted on arXiv 10 Jun 2023.

## Builds on (most cited first, 4 of 4)

- [Very Deep Convolutional Networks for Large-Scale Image Recognition](https://mlsanity.com/paper/1409.1556/) (2014)
- [Identity Mappings in Deep Residual Networks](https://mlsanity.com/paper/1603.05027/) (2016)
- [Brain Tumor Segmentation using Enhanced U-Net Model with Empirical Analysis](https://mlsanity.com/paper/2210.13336/) (2022)
- [The Prominence of Artificial Intelligence in COVID-19](https://mlsanity.com/paper/2111.09537/) (2021)

## Built on by (most cited first, 1 of 1)

- [MOSAIC: A Multi-View 2.5D Organ Slice Selector with Cross-Attentional Reasoning for Anatomically-Aware CT Localization in Medical Organ Segmentation](https://mlsanity.com/paper/2505.10672/) (2025)

## Abstract (arXiv)

Medical imaging plays an important role in the medical sector in identifying diseases. X-ray, computed tomography (CT) scans, and magnetic resonance imaging (MRI) are a few examples of medical imaging. Most of the time, these imaging techniques are utilized to examine and diagnose diseases. Medical professionals identify the problem after analyzing the images. However, manual identification can be challenging because the human eye is not always able to recognize complex patterns in an image. Because of this, it is difficult for any professional to recognize a disease with rapidity and accuracy. In recent years, medical professionals have started adopting Computer-Aided Diagnosis (CAD) systems to evaluate medical images. This system can analyze the image and detect the disease very precisely and quickly. However, this system has certain drawbacks in that it needs to be processed before analysis. Medical research is already entered a new era of research which is called Artificial Intelligence (AI). AI can automatically find complex patterns from an image and identify diseases. Methods for medical imaging that uses AI techniques will be covered in this chapter.