AIMC Topic: Image Processing, Computer-Assisted

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Imaging-based deep learning in liver diseases.

Chinese medical journal Jun 5, 2022
Liver Deep Learning Liver Diseases Image Processing, Computer-Assisted Humans
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A Prior Knowledge-Guided, Deep Learning-Based Semiautomatic Segmentation for Complex Anatomy on Magnetic Resonance Imaging.

International journal of radiation oncology, biology, physics Jun 4, 2022
PURPOSE: Despite recent substantial improvement in autosegmentation using deep learning (DL) methods, labor-intensive and time-consuming slice-by-slice manual editing is often needed, particularly for complex anatomy (eg, abdominal organs). This work...
Magnetic Resonance Imaging Radiotherapy, Image-Guided Deep Learning Image Processing, Computer-Assisted Humans
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Machine learning-based protein crystal detection for monitoring of crystallization processes enabled with large-scale synthetic data sets of photorealistic images.

Analytical and bioanalytical chemistry Jun 4, 2022
Since preparative chromatography is a sustainability challenge due to large amounts of consumables used in downstream processing of biomolecules, protein crystallization offers a promising alternative as a purification method. While the limited cryst...
Image Processing, Computer-Assisted Proteins Crystallization Machine Learning Algorithms Neural Networks, Computer
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Automatic head computed tomography image noise quantification with deep learning.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB) Jun 4, 2022
PURPOSE: Computed tomography (CT) image noise is usually determined by standard deviation (SD) of pixel values from uniform image regions. This study investigates how deep learning (DL) could be applied in head CT image noise estimation.
Head Deep Learning Humans Image Processing, Computer-Assisted Neural Networks, Computer Tomography, X-Ray Computed
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Automated segmentation of head CT scans for computer-assisted craniomaxillofacial surgery applying a hierarchical patch-based stack of convolutional neural networks.

International journal of computer assisted radiology and surgery Jun 3, 2022
PURPOSE: Computer-assisted techniques play an important role in craniomaxillofacial surgery. As segmentation of three-dimensional medical imaging represents a cornerstone for these procedures, the present study was aiming at investigating a deep lear...
Computers Tomography, X-Ray Computed Imaging, Three-Dimensional Image Processing, Computer-Assisted Humans Neural Networks, Computer
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End-systole and end-diastole detection in short axis cine MRI using a fully convolutional neural network with dilated convolutions.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Jun 3, 2022
The correct assessment and characterization of heart anatomy and functionality is usually done through inspection of magnetic resonance image cine sequences. In the clinical setting it is especially important to determine the state of the left ventri...
Heart Systole Magnetic Resonance Imaging Neural Networks, Computer Diastole Magnetic Resonance Imaging, Cine Image Processing, Computer-Assisted
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Image Segmentation Using Deep Learning: A Survey.

IEEE transactions on pattern analysis and machine intelligence Jun 3, 2022
Image segmentation is a key task in computer vision and image processing with important applications such as scene understanding, medical image analysis, robotic perception, video surveillance, augmented reality, and image compression, among others, ...
Neural Networks, Computer Robotics Algorithms Deep Learning Image Processing, Computer-Assisted
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APANet: Auto-Path Aggregation for Future Instance Segmentation Prediction.

IEEE transactions on pattern analysis and machine intelligence Jun 3, 2022
Despite the remarkable progress achieved in conventional instance segmentation, the problem of predicting instance segmentation results for unobserved future frames remains challenging due to the unobservability of future data. Existing methods mainl...
Algorithms Learning Neural Networks, Computer Image Processing, Computer-Assisted
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See-Through Vision With Unsupervised Scene Occlusion Reconstruction.

IEEE transactions on pattern analysis and machine intelligence Jun 3, 2022
Among the greatest of the challenges of minimally invasive surgery (MIS) is the inadequate visualisation of the surgical field through keyhole incisions. Moreover, occlusions caused by instruments or bleeding can completely obfuscate anatomical landm...
Algorithms Image Processing, Computer-Assisted Neural Networks, Computer
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Assessment of low-dose paranasal sinus CT imaging using a new deep learning image reconstruction technique in children compared to adaptive statistical iterative reconstruction V (ASiR-V).

BMC medical imaging Jun 3, 2022
PURPOSE: To compare the effects of deep learning image reconstruction (DLIR) and adaptive statistical iterative reconstruction V (ASiR-V) on image quality in low-dose computed tomography (CT) of paranasal sinuses in children.
Retrospective Studies Tomography, X-Ray Computed Algorithms Image Processing, Computer-Assisted Double-Blind Method Deep Learning Child Humans Paranasal Sinuses Radiation Dosage Radiographic Image Interpretation, Computer-Assisted
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