AIMC Topic: Deep Learning
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AG-MS3D-CNN multiscale attention guided 3D convolutional neural network for robust brain tumor segmentation across MRI protocols.
Scientific reports
Jul 7, 2025
Accurate segmentation of brain tumors from multimodal Magnetic Resonance Imaging (MRI) plays a critical role in diagnosis, treatment planning, and disease monitoring in neuro-oncology. Traditional methods of tumor segmentation, often manual and labou...
An enhanced fusion of transfer learning models with optimization based clinical diagnosis of lung and colon cancer using biomedical imaging.
Scientific reports
Jul 7, 2025
Lung and colon cancers (LCC) are among the foremost reasons for human death and disease. Early analysis of this disorder contains various tests, namely ultrasound (US), magnetic resonance imaging (MRI), and computed tomography (CT). Despite analytica...
Automated cell annotation and classification on histopathology for spatial biomarker discovery.
Nature communications
Jul 7, 2025
Histopathology with hematoxylin and eosin (H&E) staining is routinely employed for clinical diagnoses. Single-cell analysis of histopathology provides a powerful tool for understanding the intricate cellular interactions underlying disease progressio...
Vibration-based gearbox fault diagnosis using a multi-scale convolutional neural network with depth-wise feature concatenation.
PloS one
Jul 7, 2025
This article proposes a novel approach for vibration-based gearbox fault diagnosis using a multi-scale convolutional neural network with depth-wise feature concatenation named MixNet. In industrial environments where equipment reliability directly im...
Air-ground collaborative multi-source orbital integrated detection system: Combining 3D imaging and intrusion recognition.
PloS one
Jul 7, 2025
With the rapid expansion of railway networks globally, ensuring rail infrastructure safety through efficient detection methods has become critical. Traditional inspection systems face limitations in flexibility, adaptability to adverse weather, and m...
Saliency-enhanced infrared and visible image fusion via sub-window variance filter and weighted least squares optimization.
PloS one
Jul 7, 2025
This paper proposes a novel method for infrared and visible image fusion (IVIF) to address the limitations of existing techniques in enhancing salient features and improving visual clarity. The method employs a sub-window variance filter (SVF) based ...
Video swin-CLSTM transformer: Enhancing human action recognition with optical flow and long-term dependencies.
PloS one
Jul 7, 2025
As video data volumes soar exponentially, the significance of video content analysis, particularly Human Action Recognition (HAR), has become increasingly prominent in fields such as intelligent surveillance, sports analytics, medical rehabilitation,...
Automated facial nerve identification in microsurgery with an improved unet.
Journal of robotic surgery
Jul 6, 2025
To develop a deep-learning model that improves the segmentation and detection of Facial Nerve in microsurgery, thereby increasing surgical precision and safety. We collected videos from 25 patients undergoing facial nerve decompression microsurgery. ...
A deep learning model for preoperative risk stratification of pancreatic ductal adenocarcinoma based on genomic predictors of liver metastasis.
European journal of cancer (Oxford, England : 1990)
Jul 5, 2025
BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) frequently presents with occult metastatic disease which can undermine the benefit of local treatment. Improved preoperative tools may enhance risk stratification.
Diff-SE: A Diffusion-Augmented Contrastive Learning Framework for Super-Enhancer Prediction.
Journal of chemical information and modeling
Jul 4, 2025
Super-enhancers (SEs) are cis-regulatory elements that play crucial roles in gene expression and are implicated in diseases such as cancer and Alzheimer's. Traditional identification methods rely on ChIP-seq experiments, which are costly and time-con...
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