AIMC Topic: Image Processing, Computer-Assisted

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Computed tomography (CT)-compatible remote center of motion needle steering robot: Fusing CT images and electromagnetic sensor data.

Medical engineering & physics
Lung cancer is the most common cause of cancer-related death, and early detection can reduce the mortality rate. Patients with lung nodules greater than 10 mm usually undergo a computed tomography (CT)-guided biopsy. However, aligning the needle with...

Precision Radiology: Predicting longevity using feature engineering and deep learning methods in a radiomics framework.

Scientific reports
Precision medicine approaches rely on obtaining precise knowledge of the true state of health of an individual patient, which results from a combination of their genetic risks and environmental exposures. This approach is currently limited by the lac...

Scanning double-sided documents without incurring show-through by learning to fuse two complementary images using multilayer perceptron.

PloS one
This paper presents a novel method for scanning duplex-printed documents without incurring the unwanted show-through artifact. The proposed method achieves the goal of eliminating the leaked-out reverse-side content by fusing a white backed scan imag...

Trunk-Branch Ensemble Convolutional Neural Networks for Video-Based Face Recognition.

IEEE transactions on pattern analysis and machine intelligence
Human faces in surveillance videos often suffer from severe image blur, dramatic pose variations, and occlusion. In this paper, we propose a comprehensive framework based on Convolutional Neural Networks (CNN) to overcome challenges in video-based fa...

A shallow convolutional neural network for blind image sharpness assessment.

PloS one
Blind image quality assessment can be modeled as feature extraction followed by score prediction. It necessitates considerable expertise and efforts to handcraft features for optimal representation of perceptual image quality. This paper addresses bl...

3D fully convolutional networks for subcortical segmentation in MRI: A large-scale study.

NeuroImage
This study investigates a 3D and fully convolutional neural network (CNN) for subcortical brain structure segmentation in MRI. 3D CNN architectures have been generally avoided due to their computational and memory requirements during inference. We ad...

Deeply Learned View-Invariant Features for Cross-View Action Recognition.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Classifying human actions from varied views is challenging due to huge data variations in different views. The key to this problem is to learn discriminative view-invariant features robust to view variations. In this paper, we address this problem by...

VoxResNet: Deep voxelwise residual networks for brain segmentation from 3D MR images.

NeuroImage
Segmentation of key brain tissues from 3D medical images is of great significance for brain disease diagnosis, progression assessment and monitoring of neurologic conditions. While manual segmentation is time-consuming, laborious, and subjective, aut...

Fuzzy spectral clustering for automated delineation of chronic wound region using digital images.

Computers in biology and medicine
Chronic wound is an abnormal disease condition of localized injury to the skin and its underlying tissues having physiological impaired healing response. Assessment and management of such wound is a significant burden on the healthcare system. Curren...

A Fast SVM-Based Tongue's Colour Classification Aided by -Means Clustering Identifiers and Colour Attributes as Computer-Assisted Tool for Tongue Diagnosis.

Journal of healthcare engineering
In tongue diagnosis, colour information of tongue body has kept valuable information regarding the state of disease and its correlation with the internal organs. Qualitatively, practitioners may have difficulty in their judgement due to the instable ...