Summary of Assessing Cardiomegaly in Dogs Using a Simple Cnn Model, by Nikhil Deekonda
Assessing Cardiomegaly in Dogs Using a Simple CNN Model
by Nikhil Deekonda
First submitted to arxiv on: 8 Jul 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Machine Learning (cs.LG); Image and Video Processing (eess.IV)
GrooveSquid.com Paper Summaries
GrooveSquid.com’s goal is to make artificial intelligence research accessible by summarizing AI papers in simpler terms. Each summary below covers the same AI paper, written at different levels of difficulty. The medium difficulty and low difficulty versions are original summaries written by GrooveSquid.com, while the high difficulty version is the paper’s original abstract. Feel free to learn from the version that suits you best!
| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper presents DogHeart, a dataset containing 2400 images of dog hearts classified as small, normal, or large based on VHS score. A custom convolutional neural network (CNN) model is designed with four convolutional layers and four fully connected layers. Notably, the model achieves high accuracy in classifying cardiomegaly severity despite not using data augmentation techniques. The study showcases the potential of automated cardiac condition assessment in dogs, enabling early detection and intervention in veterinary care. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper creates a new dataset called DogHeart with lots of pictures of dog hearts. They’re grouped into three categories: small, normal, or large. To analyze these images, they built a special kind of computer program (CNN) that uses patterns to recognize what’s going on. This program is pretty good at figuring out if the heart is healthy or not, even without changing the pictures or using extra information. The researchers think this can help us learn more about dogs’ hearts and find problems early so we can do something about it. |
Keywords
* Artificial intelligence * Cnn * Data augmentation * Neural network
