AIMC Topic: Image Processing, Computer-Assisted

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Automatic feature learning using multichannel ROI based on deep structured algorithms for computerized lung cancer diagnosis.

Computers in biology and medicine
This study aimed to analyze the ability of extracting automatically generated features using deep structured algorithms in lung nodule CT image diagnosis, and compare its performance with traditional computer aided diagnosis (CADx) systems using hand...

Learning a Deep Model for Human Action Recognition from Novel Viewpoints.

IEEE transactions on pattern analysis and machine intelligence
Recognizing human actions from unknown and unseen (novel) views is a challenging problem. We propose a Robust Non-Linear Knowledge Transfer Model (R-NKTM) for human action recognition from novel views. The proposed R-NKTM is a deep fully-connected ne...

Epithelium-Stroma Classification via Convolutional Neural Networks and Unsupervised Domain Adaptation in Histopathological Images.

IEEE journal of biomedical and health informatics
Epithelium-stroma classification is a necessary preprocessing step in histopathological image analysis. Current deep learning based recognition methods for histology data require collection of large volumes of labeled data in order to train a new neu...

Artificial Neural Networks in Image Processing for Early Detection of Breast Cancer.

Computational and mathematical methods in medicine
Medical imaging techniques have widely been in use in the diagnosis and detection of breast cancer. The drawback of applying these techniques is the large time consumption in the manual diagnosis of each image pattern by a professional radiologist. A...

Feasibility of spirography features for objective assessment of motor function in Parkinson's disease.

Artificial intelligence in medicine
OBJECTIVE: Parkinson's disease (PD) is currently incurable, however proper treatment can ease the symptoms and significantly improve the quality of life of patients. Since PD is a chronic disease, its efficient monitoring and management is very impor...

SLIDE: automatic spine level identification system using a deep convolutional neural network.

International journal of computer assisted radiology and surgery
PURPOSE: Percutaneous spinal needle insertion procedures often require proper identification of the vertebral level to effectively and safely deliver analgesic agents. The current clinical method involves "blind" identification of the vertebral level...

Ultrasound Standard Plane Detection Using a Composite Neural Network Framework.

IEEE transactions on cybernetics
Ultrasound (US) imaging is a widely used screening tool for obstetric examination and diagnosis. Accurate acquisition of fetal standard planes with key anatomical structures is very crucial for substantial biometric measurement and diagnosis. However...

Addressing multi-label imbalance problem of surgical tool detection using CNN.

International journal of computer assisted radiology and surgery
PURPOSE: A fully automated surgical tool detection framework is proposed for endoscopic video streams. State-of-the-art surgical tool detection methods rely on supervised one-vs-all or multi-class classification techniques, completely ignoring the co...

Immunological Approach for Full NURBS Reconstruction of Outline Curves from Noisy Data Points in Medical Imaging.

IEEE/ACM transactions on computational biology and bioinformatics
Curve reconstruction from data points is an important issue for advanced medical imaging techniques, such as computer tomography (CT) and magnetic resonance imaging (MRI). The most powerful fitting functions for this purpose are the NURBS (non-unifor...