AIMC Journal:
Medical image analysis

Showing 441 to 450 of 684 articles

Automated diagnosis of bone metastasis based on multi-view bone scans using attention-augmented deep neural networks.

Medical image analysis Jul 18, 2020
Bone scintigraphy is accepted as an effective diagnostic tool for whole-body examination of bone metastasis. However, the manual analysis of bone scintigraphy images requires extensive experience and is exhausting and time-consuming. An automated dia...
Humans Neural Networks, Computer Reproducibility of Results Attention
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Time-distanced gates in long short-term memory networks.

Medical image analysis Jul 18, 2020
The Long Short-Term Memory (LSTM) network is widely used in modeling sequential observations in fields ranging from natural language processing to medical imaging. The LSTM has shown promise for interpreting computed tomography (CT) in lung screening...
Humans Neural Networks, Computer Algorithms Tomography, X-Ray Computed Natural Language Processing
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Triple U-net: Hematoxylin-aware nuclei segmentation with progressive dense feature aggregation.

Medical image analysis Jul 18, 2020
Nuclei segmentation is a vital step for pathological cancer research. It is still an open problem due to some difficulties, such as color inconsistency introduced by non-uniform manual operations, blurry tumor nucleus boundaries and overlapping tumor...
Neural Networks, Computer Staining and Labeling Cell Nucleus Eosine Yellowish-(YS) Hematoxylin
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Cascaded one-shot deformable convolutional neural networks: Developing a deep learning model for respiratory motion estimation in ultrasound sequences.

Medical image analysis Jul 18, 2020
Improving the quality of image-guided radiation therapy requires the tracking of respiratory motion in ultrasound sequences. However, the low signal-to-noise ratio and the artifacts in ultrasound images make it difficult to track targets accurately a...
Humans Neural Networks, Computer Deep Learning Ultrasonography Motion Radiotherapy, Image-Guided
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NuClick: A deep learning framework for interactive segmentation of microscopic images.

Medical image analysis Jul 10, 2020
Object segmentation is an important step in the workflow of computational pathology. Deep learning based models generally require large amount of labeled data for precise and reliable prediction. However, collecting labeled data is expensive because ...
Humans Deep Learning Image Processing, Computer-Assisted Histological Techniques
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Deep learning based HEp-2 image classification: A comprehensive review.

Medical image analysis Jul 7, 2020
Classification of HEp-2 cell patterns plays a significant role in the indirect immunofluorescence test for identifying autoimmune diseases in the human body. Many automatic HEp-2 cell classification methods have been proposed in recent years, amongst...
Humans Deep Learning Image Processing, Computer-Assisted Fluorescent Antibody Technique, Indirect
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Weakly supervised object detection with 2D and 3D regression neural networks.

Medical image analysis Jun 30, 2020
Finding automatically multiple lesions in large images is a common problem in medical image analysis. Solving this problem can be challenging if, during optimization, the automated method cannot access information about the location of the lesions no...
Humans Neural Networks, Computer Brain Magnetic Resonance Imaging
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Uncertainty-aware multi-view co-training for semi-supervised medical image segmentation and domain adaptation.

Medical image analysis Jun 27, 2020
Although having achieved great success in medical image segmentation, deep learning-based approaches usually require large amounts of well-annotated data, which can be extremely expensive in the field of medical image analysis. Unlabeled data, on the...
Humans Supervised Machine Learning Uncertainty
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Spatio-temporal visual attention modelling of standard biometry plane-finding navigation.

Medical image analysis Jun 20, 2020
We present a novel multi-task neural network called Temporal SonoEyeNet (TSEN) with a primary task to describe the visual navigation process of sonographers by learning to generate visual attention maps of ultrasound images around standard biometry p...
Humans Neural Networks, Computer Ultrasonography Head Biometry
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Deep learning with noisy labels: Exploring techniques and remedies in medical image analysis.

Medical image analysis Jun 20, 2020
Supervised training of deep learning models requires large labeled datasets. There is a growing interest in obtaining such datasets for medical image analysis applications. However, the impact of label noise has not received sufficient attention. Rec...
Humans Machine Learning Deep Learning Image Processing, Computer-Assisted Diagnostic Imaging Observer Variation
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