AIMC Topic: Image Processing, Computer-Assisted

Clear Filters Showing 8421 to 8430 of 10288 articles

A convolutional autoencoder approach for mining features in cellular electron cryo-tomograms and weakly supervised coarse segmentation.

Journal of structural biology
Cellular electron cryo-tomography enables the 3D visualization of cellular organization in the near-native state and at submolecular resolution. However, the contents of cellular tomograms are often complex, making it difficult to automatically isola...

Deep Convolutional Neural Networks Enable Discrimination of Heterogeneous Digital Pathology Images.

EBioMedicine
Pathological evaluation of tumor tissue is pivotal for diagnosis in cancer patients and automated image analysis approaches have great potential to increase precision of diagnosis and help reduce human error. In this study, we utilize several computa...

Deep Visual Attention Prediction.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
In this paper, we aim to predict human eye fixation with view-free scenes based on an end-to-end deep learning architecture. Although convolutional neural networks (CNNs) have made substantial improvement on human attention prediction, it is still ne...

Ultrasound Characterization of Bone Demineralization Using a Support Vector Machine.

Ultrasound in medicine & biology
We propose an ultrasound-guided remote measurement technique, utilizing an acoustic radiation force beam as our excitation source and a receiving hydrophone, to assess non-invasively a bone's mechanical properties. Features, such as velocity, were ex...

[Advantages and Application Prospects of Deep Learning in Image Recognition and Bone Age Assessment].

Fa yi xue za zhi
Deep learning and neural network models have been new research directions and hot issues in the fields of machine learning and artificial intelligence in recent years. Deep learning has made a breakthrough in the applications of image and speech reco...

Automated tongue diagnosis on the smartphone and its applications.

Computer methods and programs in biomedicine
Tongue features are important objective basis for clinical diagnosis and treatment in both western medicine and Chinese medicine. The need for continuous monitoring of health conditions inspires us to develop an automatic tongue diagnosis system base...

Metric learning with spectral graph convolutions on brain connectivity networks.

NeuroImage
Graph representations are often used to model structured data at an individual or population level and have numerous applications in pattern recognition problems. In the field of neuroscience, where such representations are commonly used to model str...

Extraction, selection and comparison of features for an effective automated computer-aided diagnosis of Parkinson's disease based on [I]FP-CIT SPECT images.

European journal of nuclear medicine and molecular imaging
PURPOSE: This work aimed to assess the potential of a set of features extracted from [I]FP-CIT SPECT brain images to be used in the computer-aided "in vivo" confirmation of dopaminergic degeneration and therefore to assist clinical decision to diagno...

Neuroanatomical heterogeneity of schizophrenia revealed by semi-supervised machine learning methods.

Schizophrenia research
UNLABELLED: Schizophrenia is associated with heterogeneous clinical symptoms and neuroanatomical alterations. In this work, we aim to disentangle the patterns of neuroanatomical alterations underlying a heterogeneous population of patients using a se...

Using diffusion MRI to discriminate areas of cortical grey matter.

NeuroImage
Cortical area parcellation is a challenging problem that is often approached by combining structural imaging (e.g., quantitative T1, diffusion-based connectivity) with functional imaging (e.g., task activations, topological mapping, resting state cor...