U-Net in Medical Image Segmentation: A Review of Its Applications Across Modalities
Medical imaging is essential in healthcare to provide key insights into patient anatomy and
pathology, aiding in diagnosis and treatment. Non-invasive techniques such as X-ray …
pathology, aiding in diagnosis and treatment. Non-invasive techniques such as X-ray …
Polynomial-SHAP analysis of liver disease markers for capturing of complex feature interactions in machine learning models
Liver disease diagnosis is pivotal for effective patient management, and machine learning
techniques have shown promise in this domain. In this study, we investigate the impact of …
techniques have shown promise in this domain. In this study, we investigate the impact of …
Explainable attention based breast tumor segmentation using a combination of UNet, ResNet, DenseNet, and EfficientNet models
This study utilizes the Breast Ultrasound Image (BUSI) dataset to present a deep learning
technique for breast tumor segmentation based on a modified UNet architecture. To improve …
technique for breast tumor segmentation based on a modified UNet architecture. To improve …
ATEDU-NET: An Attention-Embedded Deep Unet for multi-disease diagnosis in chest X-ray images, breast ultrasound, and retina fundus
In image segmentation for medical image analysis, effective upsampling is crucial for
recovering spatial information lost during downsampling. This challenge becomes more …
recovering spatial information lost during downsampling. This challenge becomes more …