AIMC Topic: Image Processing, Computer-Assisted

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Automated methods for sella turcica segmentation on cephalometric radiographic data using deep learning (CNN) techniques.

Oral radiology
OBJECTIVE: The objective of this work is to present a novel technique using convolutional neural network (CNN) architectures for automatic segmentation of sella turcica (ST) on cephalometric radiographic image dataset. The proposed work suggests poss...

Eliminating CT radiation for clinical PET examination using deep learning.

European journal of radiology
Clinical PET/CT examinations rely on CT modality for anatomical localization and attenuation correction of the PET data. However, the use of CT significantly increases the risk of ionizing radiation exposure for patients. We propose a deep learning f...

Effective Free-Driving Region Detection for Mobile Robots by Uncertainty Estimation Using RGB-D Data.

Sensors (Basel, Switzerland)
Accurate segmentation of drivable areas and road obstacles is critical for autonomous mobile robots to navigate safely in indoor and outdoor environments. With the fast advancement of deep learning, mobile robots may now perform autonomous navigation...

A deep learning based CT image analytics protocol to identify lung adenocarcinoma category and high-risk tumor area.

STAR protocols
We present a protocol which implements deep learning-based identification of the lung adenocarcinoma category with high accuracy and generalizability, and labeling of the high-risk area on Computed Tomography (CT) images. The protocol details the exe...

Moving Object Detection Based on Fusion of Depth Information and RGB Features.

Sensors (Basel, Switzerland)
The detection of moving objects is one of the key problems in the field of computer vision. It is very important to detect moving objects accurately and rapidly for automatic driving. In this paper, we propose an improved moving object detection meth...

CAM-Wnet: An effective solution for accurate pulmonary embolism segmentation.

Medical physics
BACKGROUND: The morbidity of pulmonary embolism (PE) is only lower than that of coronary heart disease and hypertension. Early detection, early diagnosis, and timely treatment are the keys to effectively reduce the risk of death. Nevertheless, PE seg...

PRAPNet: A Parallel Residual Atrous Pyramid Network for Polyp Segmentation.

Sensors (Basel, Switzerland)
In a colonoscopy, accurate computer-aided polyp detection and segmentation can help endoscopists to remove abnormal tissue. This reduces the chance of polyps developing into cancer, which is of great importance. In this paper, we propose a neural net...

Development of Deep-Learning-Based Single-Molecule Localization Image Analysis.

International journal of molecular sciences
Recent developments in super-resolution fluorescence microscopic techniques (SRM) have allowed for nanoscale imaging that greatly facilitates our understanding of nanostructures. However, the performance of single-molecule localization microscopy (SM...

Fuzzy Medical Computer Vision Image Restoration and Visual Application.

Computational and mathematical methods in medicine
In order to shorten the image registration time and improve the imaging quality, this paper proposes a fuzzy medical computer vision image information recovery algorithm based on the fuzzy sparse representation algorithm. Firstly, by constructing a c...