AIMC Topic: Algorithms

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Detecting Brain Tumor using Machines Learning Techniques Based on Different Features Extracting Strategies.

Current medical imaging reviews
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...

An Intensity Variation Pattern Analysis Based Machine Learning Classifier for MRI Brain Tumor Detection.

Current medical imaging reviews
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, ...

Three Dimensional Analysis of SPECT Images for Diagnosing Early Parkinson's Disease using Radial Basis Function Kernel - Extreme Learning Machine.

Current medical imaging reviews
BACKGROUND: Parkinson's Disease (PD) is caused by the deficiency of dopamine, the neurotransmitter that has an effect on specific uptake region of the substantia nigra. Identification of PD is quite tough at an early stage.

Image Based Brain Segmentation: From Multi-Atlas Fusion to Deep Learning.

Current medical imaging reviews
BACKGROUND: This review aims to identify the development of the algorithms for brain tissue and structure segmentation in MRI images.

Semi-dynamic Control of FCM Initialization for Automatic Extraction of Inflamed Appendix from Ultrasonography.

Current medical imaging reviews
BACKGROUND: Current naked-eye examination of the ultrasound images for inflamed appendix has limitations due to its intrinsic operator subjectivity problem.

Categorization & Recognition of Lung Tumor Using Machine Learning Representations.

Current medical imaging reviews
BACKGROUND: Lung Cancer is the disease spreading around the world nowadays. Early recognition of lung disease is a difficult task as the cells which cause tumor will grow quickly and the majority of these cells are enclosed with each other. From the ...

LNTP-MDBN: Big Data Integrated Learning Framework for Heterogeneous Image Set Classification.

Current medical imaging reviews
BACKGROUND: With the explosive growth of global data, the term Big Data describes the enormous size of dataset through the detailed analysis. The big data analytics revealed the hidden patterns and secret correlations among the values. The major chal...

A Hybrid Approach for Sub-Acute Ischemic Stroke Lesion Segmentation Using Random Decision Forest and Gravitational Search Algorithm.

Current medical imaging reviews
BACKGROUND: The sub-acute ischemic stroke is the most basic illnesses reason for death on the planet. We evaluate the impact of segmentation technique during the time of breaking down the capacities of the cerebrum.

Alzheimer's Disease Classification Based on Multi-feature Fusion.

Current medical imaging reviews
BACKGROUND: In this study, we investigated the fusion of texture and morphometric features as a possible diagnostic biomarker for Alzheimer's Disease (AD).

A general approach for improving deep learning-based medical relation extraction using a pre-trained model and fine-tuning.

Database : the journal of biological databases and curation
The automatic extraction of meaningful relations from biomedical literature or clinical records is crucial in various biomedical applications. Most of the current deep learning approaches for medical relation extraction require large-scale training d...