AIMC Topic: Image Processing, Computer-Assisted

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Deep structured learning with vision intelligence for oral carcinoma lesion segmentation and classification using medical imaging.

Scientific reports Feb 24, 2025
Oral carcinoma (OC) is a toxic illness among the most general malignant cancers globally, and it has developed a gradually significant public health concern in emerging and low-to-middle-income states. Late diagnosis, high incidence, and inadequate t...
Machine Learning Deep Learning Mouth Neoplasms Image Processing, Computer-Assisted Humans
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Data stewardship and curation practices in AI-based genomics and automated microscopy image analysis for high-throughput screening studies: promoting robust and ethical AI applications.

Human genomics Feb 23, 2025
BACKGROUND: Researchers have increasingly adopted AI and next-generation sequencing (NGS), revolutionizing genomics and high-throughput screening (HTS), and transforming our understanding of cellular processes and disease mechanisms. However, these a...
High-Throughput Screening Assays Data Curation Humans Genomics Artificial Intelligence Microscopy Image Processing, Computer-Assisted High-Throughput Nucleotide Sequencing
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TTGA U-Net: Two-stage two-stream graph attention U-Net for hepatic vessel connectivity enhancement.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Feb 22, 2025
Accurate segmentation of hepatic vessels is pivotal for guiding preoperative planning in ablation surgery utilizing CT images. While non-contrast CT images often lack observable vessels, we focus on segmenting hepatic vessels within preoperative MR i...
Magnetic Resonance Imaging Liver Hepatic Veins Hepatic Artery Algorithms Liver Neoplasms Image Processing, Computer-Assisted Humans Neural Networks, Computer
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CNN-Transformer and Channel-Spatial Attention based network for hyperspectral image classification with few samples.

Neural networks : the official journal of the International Neural Network Society Feb 22, 2025
Hyperspectral image classification is an important foundational technology in the field of Earth observation and remote sensing. In recent years, deep learning has achieved a series of remarkable achievements in this area. These deep learning-based h...
Neural Networks, Computer Image Processing, Computer-Assisted Algorithms Deep Learning Hyperspectral Imaging
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Deep Learning-Based Tumor Segmentation of Murine Magnetic Resonance Images of Prostate Cancer Patient-Derived Xenografts.

Tomography (Ann Arbor, Mich.) Feb 22, 2025
BACKGROUND/OBJECTIVE: Longitudinal in vivo studies of murine xenograft models are widely utilized in oncology to study cancer biology and develop therapies. Magnetic resonance imaging (MRI) of these tumors is an invaluable tool for monitoring tumor g...
Deep Learning Prostatic Neoplasms Image Processing, Computer-Assisted Tibia Kidney Disease Models, Animal Heterografts Magnetic Resonance Imaging Animals Liver Humans Mice Male Algorithms
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Content-Based Histopathological Image Retrieval.

Sensors (Basel, Switzerland) Feb 22, 2025
Feature descriptors in histopathological images are an important challenge for the implementation of Content-Based Image Retrieval (CBIR) systems, an essential tool to support pathologists. Deep learning models like Convolutional Neural Networks and ...
Algorithms Deep Learning Image Processing, Computer-Assisted Humans Neural Networks, Computer
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Feasibility study of texture-based machine learning approach for early detection of neonatal jaundice.

Scientific reports Feb 22, 2025
Untreated neonatal jaundice can have severe consequences. Effective screening for neonatal jaundice can prevent long-term complications in infants. Non-invasive approaches may be beneficial in settings with limited resources. This feasibility study e...
Image Processing, Computer-Assisted Support Vector Machine Feasibility Studies Infant, Newborn Male Neonatal Screening Jaundice, Neonatal Early Diagnosis Bilirubin Machine Learning Female Humans
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Enhanced recognition and counting of high-coverage Amorphophallus konjac by integrating UAV RGB imagery and deep learning.

Scientific reports Feb 22, 2025
Accurate counting of Amorphophallus konjac (Konjac) plants can offer valuable insights for agricultural management and yield prediction. While current studies have primarily focused on detecting and counting crop plants during the early stages of low...
Deep Learning Amorphophallus Remote Sensing Technology Image Processing, Computer-Assisted Agriculture Crops, Agricultural Unmanned Aerial Devices
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Semi-supervised tissue segmentation from histopathological images with consistency regularization and uncertainty estimation.

Scientific reports Feb 22, 2025
Pathologists have depended on their visual experience to assess tissue structures in smear images, which was time-consuming, error-prone, and inconsistent. Deep learning, particularly Convolutional Neural Networks (CNNs), offers the ability to automa...
Uncertainty Image Processing, Computer-Assisted Supervised Machine Learning Algorithms Humans Deep Learning Neural Networks, Computer
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SVEA: an accurate model for structural variation detection using multi-channel image encoding and enhanced AlexNet architecture.

Journal of translational medicine Feb 22, 2025
BACKGROUND: Structural variations (SVs) are a pervasive and impactful class of genetic variation within the genome, significantly influencing gene function, impacting human health, and contributing to disease. Recent advances in deep learning have sh...
Humans Neural Networks, Computer Convolutional Neural Networks Image Processing, Computer-Assisted Genomic Structural Variation Algorithms Deep Learning
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