AIMC Topic: Image Processing, Computer-Assisted

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A Multitask CNN for Near-Infrared Probe: Enhanced Real-Time Breast Cancer Imaging.

Sensors (Basel, Switzerland)
The early detection of breast cancer, particularly in dense breast tissues, faces significant challenges with traditional imaging techniques such as mammography. This study utilizes a Near-infrared Scan (NIRscan) probe and an advanced convolutional n...

Automatic identification of hard and soft tissue landmarks in cone-beam computed tomography via deep learning with diversity datasets: a methodological study.

BMC oral health
BACKGROUND: Manual landmark detection in cone beam computed tomography (CBCT) for evaluating craniofacial structures relies on medical expertise and is time-consuming. This study aimed to apply a new deep learning method to predict and locate soft an...

Multi-scale conv-attention U-Net for medical image segmentation.

Scientific reports
U-Net-based network structures are widely used in medical image segmentation. However, effectively capturing multi-scale features and spatial context information of complex organizational structures remains a challenge. To address this, we propose a ...

Phantom-based evaluation of image quality in Transformer-enhanced 2048-matrix CT imaging at low and ultralow doses.

Japanese journal of radiology
PURPOSE: To compare the quality of standard 512-matrix, standard 1024-matrix, and Swin2SR-based 2048-matrix phantom images under different scanning protocols.

Enhancing polyp classification: A comparative analysis of spatio-temporal techniques.

Medical engineering & physics
Colorectal cancer (CRC) is a major health concern, ranking as the third deadliest cancer globally. Early diagnosis of adenomatous polyps which are pre-cancerous abnormal tissue growth, is crucial for preventing CRC. Artificial intelligence-assisted n...

Novel hybrid transfer neural network for wheat crop growth stages recognition using field images.

Scientific reports
Wheat is one of the world's most widely cultivated cereal crops and is a primary food source for a significant portion of the population. Wheat goes through several distinct developmental phases, and accurately identifying these stages is essential f...

Federated learning with integrated attention multiscale model for brain tumor segmentation.

Scientific reports
Brain tumors are an extremely deadly condition and the growth of abnormal cells that have formed inside the brain causes the illness. According to studies, Magnetic Resonance Imaging (MRI) is a fundamental imaging method that is frequently used in me...

Validation of body composition parameters extracted via deep learning-based segmentation from routine computed tomographies.

Scientific reports
Sarcopenia and body composition metrics are strongly associated with patient outcomes. In this study, we developed and validated a flexible, open-access pipeline integrating available deep learning-based segmentation models with pre- and postprocessi...

Intelligent Detection and Recognition of Marine Plankton by Digital Holography and Deep Learning.

Sensors (Basel, Switzerland)
The detection, observation, recognition, and statistics of marine plankton are the basis of marine ecological research. In recent years, digital holography has been widely applied to plankton detection and recognition. However, the recording and reco...

Complex-valued neural networks to speed-up MR thermometry during hyperthermia using Fourier PD and PDUNet.

Scientific reports
Hyperthermia (HT) in combination with radio- and/or chemotherapy has become an accepted cancer treatment for distinct solid tumour entities. In HT, tumour tissue is exogenously heated to temperatures between 39 and 43 °C for 60 min. Temperature monit...