Researchers have introduced ClinFusion-Net, a hybrid deep learning model combining convolutional networks and vision transformers for explainable gastrointestinal disease classification.
Computer scientists have developed AV-MapNet, an end-to-end deep learning framework that combines multi-scale feature extraction, sequential residual refinement, and geodesic ...
Researchers evaluated black-box adversarial attacks and inference-time defenses on a deep learning model for thyroid nodule segmentation in ultrasound images.
Researchers developed MSDR-Net, a deep learning model that differentiates benign and malignant spinal tumors on T2-weighted fat-suppressed MRI scans with ...
A compact residual network called MSERNet removes JPEG compression artifacts from ovarian and carotid ultrasound images while preserving tissue textures ...
A systematic review of 16 studies finds quantum machine learning promising for medical image analysis but concludes the current evidence ...
A Chinese research team reports a new asymmetric U-Net with hybrid attention and residual dilated convolution that achieved Dice scores ...
A new framework called EvoLatent-FS uses evolutionary feature optimization before variational encoding to learn more compact and discriminative latent representations ...
A new framework uses ant colony optimization to configure a modified DeepLabV3+ network with a residual feature fusion module, reporting ...
YOLOv11 performed best in a single-center comparison using augmented clinical photographs to detect and grade nipple injuries, but the study ...
Researchers in Trieste embedded anatomical rules as logical constraints in a transformer segmentation model, boosting accuracy and morphological coherence in ...
A multimodal deep learning model that combines panoramic dental X-rays with structured patient metadata significantly outperforms image-only or metadata-only approaches ...
Researchers in the Czech Republic have built a generative adversarial network that creates synthetic breast ultrasound images to train a ...
Researchers in Würzburg developed CAFEx, a weakly supervised AI pipeline that uses an anatomical bottleneck to estimate cardiac ejection fraction ...
A new multi-stream deep learning framework called MS-AtroNet combines convolutional, state-space, wavelet, and evidential components to classify Alzheimer's MRI slices ...
Researchers at Sichuan University have developed a clinically driven framework that aligns orthodontic X-rays with facial photographs using weighted keypoint ...
A new lightweight AI framework called RAML embeds tumor subregion identity and geometric descriptors directly into its architecture, trading a ...
In an age where artificial intelligence continues to redefine medical diagnostics, a groundbreaking advancement has emerged in the realm of ...
In the rapidly evolving fields of medical imaging and preoperative planning, a groundbreaking study has emerged that significantly enhances our ...
