AI Medical Compendium Journal:
BioMed research international

Showing 131 to 140 of 314 articles

Calibration of the EBT3 Gafchromic Film Using HNN Deep Learning.

BioMed research international
To achieve a dose distribution conformal to the target volume while sparing normal tissues, intensity modulation with steep dose gradient is used for treatment planning. To successfully deliver such treatment, high spatial and dosimetric accuracy are...

An Artificial Neural Networks Model for Early Predicting In-Hospital Mortality in Acute Pancreatitis in MIMIC-III.

BioMed research international
BACKGROUND: Early and accurate evaluation of severity and prognosis in acute pancreatitis (AP), especially at the time of admission is very significant. This study was aimed to develop an artificial neural networks (ANN) model for early prediction of...

Qualitative and Quantitative MRI Analysis in IDH1 Genotype Prediction of Lower-Grade Gliomas: A Machine Learning Approach.

BioMed research international
PURPOSE: Preoperative prediction of isocitrate dehydrogenase 1 (IDH1) mutation in lower-grade gliomas (LGGs) is crucial for clinical decision-making. This study aimed to examine the predictive value of a machine learning approach using qualitative an...

Automated Classification and Segmentation in Colorectal Images Based on Self-Paced Transfer Network.

BioMed research international
Colorectal imaging improves on diagnosis of colorectal diseases by providing colorectal images. Manual diagnosis of colorectal disease is labor-intensive and time-consuming. In this paper, we present a method for automatic colorectal disease classifi...

DVH Prediction for VMAT in NPC with GRU-RNN: An Improved Method by Considering Biological Effects.

BioMed research international
PURPOSE: A recurrent neural network (RNN) and its variants such as gated recurrent unit-based RNN (GRU-RNN) were found to be very suitable for dose-volume histogram (DVH) prediction in our previously published work. Using the dosimetric information g...

QAIS-DSNN: Tumor Area Segmentation of MRI Image with Optimized Quantum Matched-Filter Technique and Deep Spiking Neural Network.

BioMed research international
Tumor segmentation in brain MRI images is a noted process that can make the tumor easier to diagnose and lead to effective radiotherapy planning. Providing and building intelligent medical systems can be considered as an aid for physicians. In many c...

FFU-Net: Feature Fusion U-Net for Lesion Segmentation of Diabetic Retinopathy.

BioMed research international
Diabetic retinopathy is one of the main causes of blindness in human eyes, and lesion segmentation is an important basic work for the diagnosis of diabetic retinopathy. Due to the small lesion areas scattered in fundus images, it is laborious to segm...

Medical Image Retrieval Using Empirical Mode Decomposition with Deep Convolutional Neural Network.

BioMed research international
Content-based medical image retrieval (CBMIR) systems attempt to search medical image database to narrow the semantic gap in medical image analysis. The efficacy of high-level medical information representation using features is a major challenge in ...

Spiculation Sign Recognition in a Pulmonary Nodule Based on Spiking Neural P Systems.

BioMed research international
The spiculation sign is one of the main signs to distinguish benign and malignant pulmonary nodules. In order to effectively extract the image feature of a pulmonary nodule for the spiculation sign distinguishment, a new spiculation sign recognition ...

NSCR-Based DenseNet for Lung Tumor Recognition Using Chest CT Image.

BioMed research international
Nonnegative sparse representation has become a popular methodology in medical analysis and diagnosis in recent years. In order to resolve network degradation, higher dimensionality in feature extraction, data redundancy, and other issues faced when m...