AIMC Topic: Image Processing, Computer-Assisted

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Cascaded atrous convolution and spatial pyramid pooling for more accurate tumor target segmentation for rectal cancer radiotherapy.

Physics in medicine and biology
Convolutional neural networks (CNNs) have become the state-of-the-art method for medical segmentation. However, repeated pooling and striding operations reduce the feature resolution, causing loss of detailed information. Additionally, tumors of diff...

Recognition of Schizophrenia with Regularized Support Vector Machine and Sequential Region of Interest Selection using Structural Magnetic Resonance Imaging.

Scientific reports
Structural brain abnormalities in schizophrenia have been well characterized with the application of univariate methods to magnetic resonance imaging (MRI) data. However, these traditional techniques lack sensitivity and predictive value at the indiv...

Improving classification of pollen grain images of the POLEN23E dataset through three different applications of deep learning convolutional neural networks.

PloS one
In palynology, the visual classification of pollen grains from different species is a hard task which is usually tackled by human operators using microscopes. Its complete automatization would save a high quantity of resources and provide valuable im...

The application of convolution neural network based cell segmentation during cryopreservation.

Cryobiology
For most of the cells, water permeability and plasma membrane properties play a vital role in the optimal protocol for successful cryopreservation. Measuring the water permeability of cells during subzero temperature is essential. So far, there is no...

Learning Generalizable Recurrent Neural Networks from Small Task-fMRI Datasets.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
Deep learning has become the new state-of-the-art for many problems in image analysis. However, large datasets are often required for such deep networks to learn effectively. This poses a difficult challenge for many medical image analysis problems i...

Iterative PET Image Reconstruction Using Convolutional Neural Network Representation.

IEEE transactions on medical imaging
PET image reconstruction is challenging due to the ill-poseness of the inverse problem and limited number of detected photons. Recently, the deep neural networks have been widely and successfully used in computer vision tasks and attracted growing in...

Feature Selection and Parameters Optimization of Support Vector Machines Based on Hybrid Glowworm Swarm Optimization for Classification of Diabetic Retinopathy.

Journal of medical systems
Diabetic Retinopathy (DR) has been a leading cause of blindness in case of human beings falling between the ages of 20 and 74 years. This will have a major influence on both the patient and the society as it can normally influence the humans in their...

Pheno-Deep Counter: a unified and versatile deep learning architecture for leaf counting.

The Plant journal : for cell and molecular biology
Direct observation of morphological plant traits is tedious and a bottleneck for high-throughput phenotyping. Hence, interest in image-based analysis is increasing, with the requirement for software that can reliably extract plant traits, such as lea...

Weakly Supervised Learning of Metric Aggregations for Deformable Image Registration.

IEEE journal of biomedical and health informatics
Deformable registration has been one of the pillars of biomedical image computing. Conventional approaches refer to the definition of a similarity criterion that, once endowed with a deformation model and a smoothness constraint, determines the optim...

Multimodal Medical Image Fusion Based on Fuzzy Discrimination With Structural Patch Decomposition.

IEEE journal of biomedical and health informatics
Multimodal medical image fusion, emerging as a hot topic, aims to fuse images with complementary multi-source information. In this paper, we propose a novel multimodal medical image fusion method based on structural patch decomposition (SPD) and fuzz...