AIMC Topic:
Brain Neoplasms

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Wavelet-enhanced convolutional neural network: a new idea in a deep learning paradigm.

Biomedizinische Technik. Biomedical engineering Apr 24, 2019
PURPOSE: Manual brain tumor segmentation is a challenging task that requires the use of machine learning techniques. One of the machine learning techniques that has been given much attention is the convolutional neural network (CNN). The performance ...
Brain Neoplasms Deep Learning Image Processing, Computer-Assisted Wavelet Analysis Humans Neural Networks, Computer Machine Learning
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Natural Language Processing for Automated Quantification of Brain Metastases Reported in Free-Text Radiology Reports.

JCO clinical cancer informatics Apr 1, 2019
PURPOSE: Although the bulk of patient-generated health data are increasing exponentially, their use is impeded because most data come in unstructured format, namely as free-text clinical reports. A variety of natural language processing (NLP) methods...
Radiology Research Report Humans Medical Informatics Algorithms ROC Curve Electronic Health Records Magnetic Resonance Imaging Reproducibility of Results Natural Language Processing Brain Neoplasms
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A platform for artificial intelligence based identification of the extravasation potential of cancer cells into the brain metastatic niche.

Lab on a chip Mar 27, 2019
Brain metastases are the most lethal complication of advanced cancer; therefore, it is critical to identify when a tumor has the potential to metastasize to the brain. There are currently no interventions that shed light on the potential of primary t...
Cell Line, Tumor Cell Separation Artificial Intelligence Phenotype Brain Neoplasms Humans
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MR-based treatment planning in radiation therapy using a deep learning approach.

Journal of applied clinical medical physics Mar 1, 2019
PURPOSE: To develop and evaluate the feasibility of deep learning approaches for MR-based treatment planning (deepMTP) in brain tumor radiation therapy.
Magnetic Resonance Imaging Stroke Radiotherapy Planning, Computer-Assisted Radiotherapy Dosage Radiotherapy, Intensity-Modulated Middle Aged Deep Learning Imaging, Three-Dimensional Adult Brain Neoplasms Male Humans Retrospective Studies Tomography, X-Ray Computed Aged, 80 and over Young Adult Female Aged
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Hybrid 11C-MET PET/MRI Combined With "Machine Learning" in Glioma Diagnosis According to the Revised Glioma WHO Classification 2016.

Clinical nuclear medicine Mar 1, 2019
PURPOSE: With the advent of the revised WHO classification from 2016, molecular features, including isocitrate dehydrogenase (IDH) mutation have become important in glioma subtyping. This pilot trial analyzed the potential for C-methionine (MET) PET/...
Humans Adult Brain Neoplasms Male Middle Aged Machine Learning Female Aged Carbon Radioisotopes Radiopharmaceuticals Glioma Positron-Emission Tomography Methionine Magnetic Resonance Imaging Multimodal Imaging
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AdaptAhead Optimization Algorithm for Learning Deep CNN Applied to MRI Segmentation.

Journal of digital imaging Feb 1, 2019
Deep learning is one of the subsets of machine learning that is widely used in artificial intelligence (AI) field such as natural language processing and machine vision. The deep convolution neural network (DCNN) extracts high-level concepts from low...
Humans Neural Networks, Computer Algorithms Brain Reproducibility of Results Deep Learning Brain Neoplasms Magnetic Resonance Imaging Image Interpretation, Computer-Assisted
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Computers turn neural signals into speech.

Science (New York, N.Y.) Jan 4, 2019
Speech Epilepsy Brain-Computer Interfaces Neural Networks, Computer Computers Brain Neoplasms Humans
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Detecting Brain Tumor using Machines Learning Techniques Based on Different Features Extracting Strategies.

Current medical imaging reviews Jan 1, 2019
BACKGROUND: Brain tumor is the leading cause of death worldwide. It is obvious that the chances of survival can be increased if the tumor is identified and properly classified at an initial stage. MRI (Magnetic Resonance Imaging) is one source of bra...
Brain Neoplasms Bayes Theorem Databases, Factual Humans Magnetic Resonance Imaging Machine Learning Retrospective Studies Decision Trees Sensitivity and Specificity Algorithms
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An Intensity Variation Pattern Analysis Based Machine Learning Classifier for MRI Brain Tumor Detection.

Current medical imaging reviews Jan 1, 2019
BACKGROUND: An accurate detection of tumor from the Magnetic Resonance Images (MRIs) is a critical and demanding task in medical image processing, due to the varying shape and structure of brain. So, different segmentation approaches such as manual, ...
Image Processing, Computer-Assisted Magnetic Resonance Imaging Humans Algorithms Machine Learning Sensitivity and Specificity Brain Neoplasms
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[An artificial neural network model for glioma grading using image information].

Zhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences Dec 28, 2018
To explore the feasibility and efficacy of artificial neural network for differentiating high-grade glioma and low-grade glioma using image information.
 Methods: A total of 130 glioma patients with confirmed pathological diagnosis were selected retr...
Humans Magnetic Resonance Imaging Neoplasm Grading Brain Neoplasms ROC Curve Glioma Neural Networks, Computer Retrospective Studies Sensitivity and Specificity
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