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Abdomen

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Image domain dual material decomposition for dual-energy CT using butterfly network.

Medical physics
PURPOSE: Dual-energy CT (DECT) has been increasingly used in imaging applications because of its capability for material differentiation. However, material decomposition suffers from magnified noise from two CT images of independent scans, leading to...

OBELISK-Net: Fewer layers to solve 3D multi-organ segmentation with sparse deformable convolutions.

Medical image analysis
Deep networks have set the state-of-the-art in most image analysis tasks by replacing handcrafted features with learned convolution filters within end-to-end trainable architectures. Still, the specifications of a convolutional network are subject to...

Changes in the expression of four ABC transporter genes in response to imidacloprid in Bemisia tabaci Q (Hemiptera: Aleyrodidae).

Pesticide biochemistry and physiology
Bemisia tabaci (Gennadius) (Hemiptera: Aleyrodidae), a globally invasive species complex that causes serious damage to field crops, has developed resistance to imidacloprid and many other pesticides. Insect detoxify to pesticides may partially depend...

Machine-learning-based automatic identification of fetal abdominal circumference from ultrasound images.

Physiological measurement
OBJECTIVE: Obstetricians mainly use ultrasound imaging for fetal biometric measurements. However, such measurements are cumbersome. Hence, there is urgent need for automatic biometric estimation. Automated analysis of ultrasound images is complicated...

Dictionary Representations for Electrode Displacement Elastography.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Ultrasound electrode displacement elastography (EDE) has demonstrated the potential to monitor ablated regions in human patients after minimally invasive microwave ablation procedures. Displacement estimation for EDE is commonly plagued by decorrelat...

Weakly Supervised Learning of Metric Aggregations for Deformable Image Registration.

IEEE journal of biomedical and health informatics
Deformable registration has been one of the pillars of biomedical image computing. Conventional approaches refer to the definition of a similarity criterion that, once endowed with a deformation model and a smoothness constraint, determines the optim...

Efficient B-Mode Ultrasound Image Reconstruction From Sub-Sampled RF Data Using Deep Learning.

IEEE transactions on medical imaging
In portable, 3-D, and ultra-fast ultrasound imaging systems, there is an increasing demand for the reconstruction of high-quality images from a limited number of radio-frequency (RF) measurements due to receiver (Rx) or transmit (Xmit) event sub-samp...

DRINet for Medical Image Segmentation.

IEEE transactions on medical imaging
Convolutional neural networks (CNNs) have revolutionized medical image analysis over the past few years. The U-Net architecture is one of the most well-known CNN architectures for semantic segmentation and has achieved remarkable successes in many di...