AIMC Topic:
Image Interpretation, Computer-Assisted
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Convergent evolution of face spaces across human face-selective neuronal groups and deep convolutional networks.
Nature communications
Oct 30, 2019
The discovery that deep convolutional neural networks (DCNNs) achieve human performance in realistic tasks offers fresh opportunities for linking neuronal tuning properties to such tasks. Here we show that the face-space geometry, revealed through pa...
Toward Automated Bladder Tumor Stratification Using Confocal Laser Endomicroscopy.
Journal of endourology
Oct 29, 2019
Urothelial carcinoma of the bladder (UCB) is the most common urinary cancer. White-light cystoscopy (WLC) forms the corner stone for the diagnosis of UCB. However, histopathological assessment is required for adjuvant treatment selection. Probe-base...
Deep Learning-Based Classification of Liver Cancer Histopathology Images Using Only Global Labels.
IEEE journal of biomedical and health informatics
Oct 28, 2019
Liver cancer is a leading cause of cancer deaths worldwide due to its high morbidity and mortality. Histopathological image analysis (HIA) is a crucial step in the early diagnosis of liver cancer and is routinely performed manually. However, this pro...
Clinical Interpretable Deep Learning Model for Glaucoma Diagnosis.
IEEE journal of biomedical and health informatics
Oct 23, 2019
Despite the potential to revolutionise disease diagnosis by performing data-driven classification, clinical interpretability of ConvNet remains challenging. In this paper, a novel clinical interpretable ConvNet architecture is proposed not only for a...
Accurate and robust segmentation of neuroanatomy in T1-weighted MRI by combining spatial priors with deep convolutional neural networks.
Human brain mapping
Oct 21, 2019
Neuroanatomical segmentation in magnetic resonance imaging (MRI) of the brain is a prerequisite for quantitative volume, thickness, and shape measurements, as well as an important intermediate step in many preprocessing pipelines. This work introduce...
Deep learning in the detection of high-grade glioma recurrence using multiple MRI sequences: A pilot study.
Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia
Oct 21, 2019
The identification of high-grade glioma (HGG) progression may pose a diagnostic dilemma due to similar appearances of treatment-related changes (TRC) (e.g. pseudoprogression or radionecrosis). Deep learning (DL) may be able to assist with this task. ...
Cascade and Fusion of Multitask Convolutional Neural Networks for Detection of Thyroid Nodules in Contrast-Enhanced CT.
Computational intelligence and neuroscience
Oct 20, 2019
With the development of computed tomography (CT), the contrast-enhanced CT scan is widely used in the diagnosis of thyroid nodules. However, due to the artifacts and high complexity of thyroid CT images, traditional machine learning has difficulty in...
A speckle-tracking strain-based artificial neural network model to differentiate cardiomyopathy type.
Scandinavian cardiovascular journal : SCJ
Oct 18, 2019
In heart failure, invasive angiography is often employed to differentiate ischaemic from non-ischaemic cardiomyopathy. We aim to examine the predictive value of echocardiographic strain features alone and in combination with other features to differ...
Image Interpretation, Computer-Assisted
Cardiomyopathies
Diagnosis, Differential
Predictive Value of Tests
Aged
Heart Failure
Prognosis
Male
Stroke Volume
Retrospective Studies
Ventricular Function, Left
Humans
Female
Echocardiography
Neural Networks, Computer
Reproducibility of Results
Middle Aged
Diagnosis, Computer-Assisted
Fully automatic segmentation of type B aortic dissection from CTA images enabled by deep learning.
European journal of radiology
Oct 17, 2019
PURPOSE: This study sought to establish a robust and fully automated Type B aortic dissection (TBAD) segmentation method by leveraging the emerging deep learning techniques.
A Super-Learner Model for Tumor Motion Prediction and Management in Radiation Therapy: Development and Feasibility Evaluation.
Scientific reports
Oct 16, 2019
In cancer radiation therapy, large tumor motion due to respiration can lead to uncertainties in tumor target delineation and treatment delivery, thus making active motion management an essential step in thoracic and abdominal tumor treatment. In curr...
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