Assessing Cardiomegaly in Dogs Using a Simple CNN Model

Nikhil Deekonda

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arXiv · 2407.06092

Assessing Cardiomegaly in Dogs Using a Simple CNN Model

Nikhil Deekonda

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Abstract

This paper introduces DogHeart, a dataset comprising 1400 training, 200 validation, and 400 test images categorized as small, normal, and large based on VHS score. A custom CNN model is developed, featuring a straightforward architecture with 4 convolutional layers and 4 fully connected layers. Despite the absence of data augmentation, the model achieves a 72\% accuracy in classifying cardiomegaly severity. The study contributes to automated assessment of cardiac conditions in dogs, highlighting the potential for early detection and intervention in veterinary care.

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Nikhil Deekonda. 2024-07-08. Assessing Cardiomegaly in Dogs Using a Simple CNN Model. https://arxiv.org/abs/2407.06092

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