Canine cardiomegaly, marked by an enlarged heart, poses serious health risks if
undetected, requiring accurate diagnostic methods. Current detection models often rely on …

Cardiomegaly is a common disease that causes the death of dogs. The field of veterinary
medicine has paid great attention to detecting dog heart abnormalities to enable the early …

The scarcity of accessible medical image data poses a significant obstacle in effectively
training deep learning models for medical diagnosis, as hospitals refrain from sharing their …

This paper introduces a convolutional neural network (CNN) model designed for image
classification tasks and evaluates its performance on the benchmark DogHeart dataset. The …

Cardiomegaly, or heart enlargement, is a significant condition in dogs requiring precise
diagnosis. This study introduces a Convolutional Neural Network (CNN) model to classify …

This paper proposes a novel approach for automated vertebral heart size point detection in
dogs using a PyTorch EfficientNetB7 object detection model. Our model leverages …

Accurate detection of canine cardiomegaly is essential for diagnosing and treating cardiac
conditions in dogs. The Vertebral Heart Score (VHS) is a standard method for evaluating …

This research report details the development and implementation of a point detection model
for measuring the Vertebral Heart Size (VHS) of dogs using X-ray images. The goal is to …

Cardiomegaly, or the enlargement of the heart, is a critical condition in dogs that requires
accurate and timely diagnosis to ensure effective treatment. This study presents a deep …

This paper presents a method for detecting keypoints in dog heart images using EfficientNet.
The aim is to accurately predict six keypoints on dog heart images, which are used to …