AIMC Topic: Image Processing, Computer-Assisted

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MRI-only based synthetic CT generation using dense cycle consistent generative adversarial networks.

Medical physics
PURPOSE: Automated synthetic computed tomography (sCT) generation based on magnetic resonance imaging (MRI) images would allow for MRI-only based treatment planning in radiation therapy, eliminating the need for CT simulation and simplifying the pati...

A cascaded dual-pathway residual network for lung nodule segmentation in CT images.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
It is difficult to obtain an accurate segmentation due to the variety of lung nodules in computed tomography (CT) images. In this study, we propose a data-driven model, called the Cascaded Dual-Pathway Residual Network (CDP-ResNet) to improve the seg...

A Multi-Sensor System for Silkworm Cocoon Gender Classification via Image Processing and Support Vector Machine.

Sensors (Basel, Switzerland)
Sericulture is traditionally a labor-intensive rural-based industry. In modern contexts, the development of process automation faces new challenges related to quality and efficiency. During the silkworm farming life cycle, a common issue is represent...

On the impact of Citizen Science-derived data quality on deep learning based classification in marine images.

PloS one
The evaluation of large amounts of digital image data is of growing importance for biology, including for the exploration and monitoring of marine habitats. However, only a tiny percentage of the image data collected is evaluated by marine biologists...

Learning image-based spatial transformations via convolutional neural networks: A review.

Magnetic resonance imaging
Recent methodological innovations in deep learning and associated advancements in computational hardware have significantly impacted the various core subfields of quantitative medical image analysis. The generalizability, computational efficiency and...

A review on brain tumor segmentation of MRI images.

Magnetic resonance imaging
The process of segmenting tumor from MRI image of a brain is one of the highly focused areas in the community of medical science as MRI is noninvasive imaging. This paper discusses a thorough literature review of recent methods of brain tumor segment...

Pathology Image Analysis Using Segmentation Deep Learning Algorithms.

The American journal of pathology
With the rapid development of image scanning techniques and visualization software, whole slide imaging (WSI) is becoming a routine diagnostic method. Accelerating clinical diagnosis from pathology images and automating image analysis efficiently and...

Enabling machine learning in X-ray-based procedures via realistic simulation of image formation.

International journal of computer assisted radiology and surgery
PURPOSE: Machine learning-based approaches now outperform competing methods in most disciplines relevant to diagnostic radiology. Image-guided procedures, however, have not yet benefited substantially from the advent of deep learning, in particular b...

A Partially-Learned Algorithm for Joint Photo-acoustic Reconstruction and Segmentation.

IEEE transactions on medical imaging
In an inhomogeneously illuminated photoacoustic image, important information like vascular geometry is not readily available, when only the initial pressure is reconstructed. To obtain the desired information, algorithms for image segmentation are of...