AIMC Topic: Imaging, Three-Dimensional

Clear Filters Showing 1381 to 1390 of 1894 articles

Fine-Tuning CNN Image Retrieval with No Human Annotation.

IEEE transactions on pattern analysis and machine intelligence
Image descriptors based on activations of Convolutional Neural Networks (CNNs) have become dominant in image retrieval due to their discriminative power, compactness of representation, and search efficiency. Training of CNNs, either from scratch or f...

Classification of Whole Mammogram and Tomosynthesis Images Using Deep Convolutional Neural Networks.

IEEE transactions on nanobioscience
Mammography is the most popular technology used for the early detection of breast cancer. Manual classification of mammogram images is a hard task because of the variability of the tumor. It yields a noteworthy number of patients being called back to...

Fully automated, real-time 3D ultrasound segmentation to estimate first trimester placental volume using deep learning.

JCI insight
We present a new technique to fully automate the segmentation of an organ from 3D ultrasound (3D-US) volumes, using the placenta as the target organ. Image analysis tools to estimate organ volume do exist but are too time consuming and operator depen...

Automatic recognition of 3D GGO CT imaging signs through the fusion of hybrid resampling and layer-wise fine-tuning CNNs.

Medical & biological engineering & computing
Ground-glass opacity (GGO) is a common CT imaging sign on high-resolution CT, which means the lesion is more likely to be malignant compared to common solid lung nodules. The automatic recognition of GGO CT imaging signs is of great importance for ea...

DeepIGeoS: A Deep Interactive Geodesic Framework for Medical Image Segmentation.

IEEE transactions on pattern analysis and machine intelligence
Accurate medical image segmentation is essential for diagnosis, surgical planning and many other applications. Convolutional Neural Networks (CNNs) have become the state-of-the-art automatic segmentation methods. However, fully automatic results may ...

Robust and semantic needle detection in 3D ultrasound using orthogonal-plane convolutional neural networks.

International journal of computer assisted radiology and surgery
PURPOSE: During needle interventions, successful automated detection of the needle immediately after insertion is necessary to allow the physician identify and correct any misalignment of the needle and the target at early stages, which reduces needl...

TernaryNet: faster deep model inference without GPUs for medical 3D segmentation using sparse and binary convolutions.

International journal of computer assisted radiology and surgery
PURPOSE: Deep convolutional neural networks (DCNN) are currently ubiquitous in medical imaging. While their versatility and high-quality results for common image analysis tasks including segmentation, localisation and prediction is astonishing, the l...

Automatic Robotic Steering of Flexible Needles from 3D Ultrasound Images in Phantoms and Ex Vivo Biological Tissue.

Annals of biomedical engineering
Robotic control of needle bending aims at increasing the precision of percutaneous procedures. Ultrasound feedback is preferable for its clinical ease of use, cost and compactness but raises needle detection issues. In this paper, we propose a comple...

Robust 3D point cloud registration based on bidirectional Maximum Correntropy Criterion.

PloS one
This paper presents a robust 3D point cloud registration algorithm based on bidirectional Maximum Correntropy Criterion (MCC). Comparing with traditional registration algorithm based on the mean square error (MSE), using the MCC is superior in dealin...

Large Scale Image Segmentation with Structured Loss Based Deep Learning for Connectome Reconstruction.

IEEE transactions on pattern analysis and machine intelligence
We present a method combining affinity prediction with region agglomeration, which improves significantly upon the state of the art of neuron segmentation from electron microscopy (EM) in accuracy and scalability. Our method consists of a 3D U-Net, t...