Deep reinforcement learning in computer vision: a comprehensive survey
Deep reinforcement learning augments the reinforcement learning framework and utilizes
the powerful representation of deep neural networks. Recent works have demonstrated the …
the powerful representation of deep neural networks. Recent works have demonstrated the …
Computational health informatics in the big data age: a survey
The explosive growth and widespread accessibility of digital health data have led to a surge
of research activity in the healthcare and data sciences fields. The conventional approaches …
of research activity in the healthcare and data sciences fields. The conventional approaches …
An anatomic transcriptional atlas of human glioblastoma
Glioblastoma is an aggressive brain tumor that carries a poor prognosis. The tumor's
molecular and cellular landscapes are complex, and their relationships to histologic features …
molecular and cellular landscapes are complex, and their relationships to histologic features …
[HTML][HTML] Integrating spatial configuration into heatmap regression based CNNs for landmark localization
In many medical image analysis applications, only a limited amount of training data is
available due to the costs of image acquisition and the large manual annotation effort …
available due to the costs of image acquisition and the large manual annotation effort …
Multi-scale deep reinforcement learning for real-time 3D-landmark detection in CT scans
Robust and fast detection of anatomical structures is a prerequisite for both diagnostic and
interventional medical image analysis. Current solutions for anatomy detection are typically …
interventional medical image analysis. Current solutions for anatomy detection are typically …
Spatial aggregation of holistically-nested convolutional neural networks for automated pancreas localization and segmentation
Accurate and automatic organ segmentation from 3D radiological scans is an important yet
challenging problem for medical image analysis. Specifically, as a small, soft, and flexible …
challenging problem for medical image analysis. Specifically, as a small, soft, and flexible …
Decision forests: A unified framework for classification, regression, density estimation, manifold learning and semi-supervised learning
Decision Forests Page 1 Decision Forests A Unified Framework for Classification,
Regression, Density Estimation, Manifold Learning and Semi-Supervised Learning Full text …
Regression, Density Estimation, Manifold Learning and Semi-Supervised Learning Full text …
Efficient human pose estimation from single depth images
We describe two new approaches to human pose estimation. Both can quickly and
accurately predict the 3D positions of body joints from a single depth image without using …
accurately predict the 3D positions of body joints from a single depth image without using …
Random forests for real time 3d face analysis
We present a random forest-based framework for real time head pose estimation from depth
images and extend it to localize a set of facial features in 3D. Our algorithm takes a voting …
images and extend it to localize a set of facial features in 3D. Our algorithm takes a voting …
Knowledge-aided convolutional neural network for small organ segmentation
Accurate and automatic organ segmentation is critical for computer-aided analysis towards
clinical decision support and treatment planning. State-of-the-art approaches have achieved …
clinical decision support and treatment planning. State-of-the-art approaches have achieved …