AIMC Topic: Image Processing, Computer-Assisted

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Deep Learning-Based Automatic Assessment of Radiation Dermatitis in Patients With Nasopharyngeal Carcinoma.

International journal of radiation oncology, biology, physics
PURPOSE: Radiation dermatitis (RD) is a common, unpleasant side effect of patients receiving radiation therapy. In clinical practice, the severity of RD is graded manually through visual inspection, which is labor intensive and often leads to large i...

Improving segmentation and classification of renal tumors in small sample 3D CT images using transfer learning with convolutional neural networks.

International journal of computer assisted radiology and surgery
PURPOSE: Computed tomography (CT) images can display internal organs of patients and are particularly suitable for preoperative surgical diagnoses. The increasing demands for computer-aided systems in recent years have facilitated the development of ...

Cell segmentation for immunofluorescence multiplexed images using two-stage domain adaptation and weakly labeled data for pre-training.

Scientific reports
Cellular profiling with multiplexed immunofluorescence (MxIF) images can contribute to a more accurate patient stratification for immunotherapy. Accurate cell segmentation of the MxIF images is an essential step. We propose a deep learning pipeline t...

BC-DUnet-based segmentation of fine cracks in bridges under a complex background.

PloS one
Crack is the external expression form of potential safety risks in bridge construction. Currently, automatic detection and segmentation of bridge cracks remains the top priority of civil engineers. With the development of image segmentation technique...

Image Inpainting With Local and Global Refinement.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Image inpainting has made remarkable progress with recent advances in deep learning. Popular networks mainly follow an encoder-decoder architecture (sometimes with skip connections) and possess sufficiently large receptive field, i.e., larger than th...

Head and neck synthetic CT generated from ultra-low-dose cone-beam CT following Image Gently Protocol using deep neural network.

Medical physics
PURPOSE: Image guidance is used to improve the accuracy of radiation therapy delivery but results in increased dose to patients. This is of particular concern in children who need be treated per Pediatric Image Gently Protocols due to long-term risks...

Attention Module Magnetic Flux Leakage Linked Deep Residual Network for Pipeline In-Line Inspection.

Sensors (Basel, Switzerland)
Pipeline operational safety is the foundation of the pipeline industry. Inspection and evaluation of defects is an important means of ensuring the safe operation of pipelines. In-line inspection of Magnetic Flux Leakage (MFL) can be used to identify ...

Deep learning tools and modeling to estimate the temporal expression of cell cycle proteins from 2D still images.

PLoS computational biology
Automatic characterization of fluorescent labeling in intact mammalian tissues remains a challenge due to the lack of quantifying techniques capable of segregating densely packed nuclei and intricate tissue patterns. Here, we describe a powerful deep...

A deep learning framework for real-time 3D model registration in robot-assisted laparoscopic surgery.

The international journal of medical robotics + computer assisted surgery : MRCAS
INTRODUCTION: The current study presents a deep learning framework to determine, in real-time, position and rotation of a target organ from an endoscopic video. These inferred data are used to overlay the 3D model of patient's organ over its real cou...