and Dorin Comaniciu1 (1) Imaging and Computer Vision, Siemens Corporate Technology, Princeton, NJ, USA Abstract In this chapter, we present an automatic object detection and segmentation framework based on Marginal…
and Dorin Comaniciu1 (1) Imaging and Computer Vision, Siemens Corporate Technology, Princeton, NJ, USA Abstract To improve the shape initialization accuracy, this chapter presents the computation of an optimal mean…
and Dorin Comaniciu1 (1) Imaging and Computer Vision, Siemens Corporate Technology, Princeton, NJ, USA Abstract This chapter presents an efficient 3D learning-based object detection method, called Marginal Space Learning (MSL)….
and Dorin Comaniciu1 (1) Imaging and Computer Vision, Siemens Corporate Technology, Princeton, NJ, USA Abstract Marginal Space Learning (MSL) has been extensively tested on multiple anatomical structure detection and segmentation…
and Dorin Comaniciu1 (1) Imaging and Computer Vision, Siemens Corporate Technology, Princeton, NJ, USA Abstract The computational framework of Marginal Space Learning (MSL) formulates the detection of an anatomical structure…
and Dorin Comaniciu1 (1) Imaging and Computer Vision, Siemens Corporate Technology, Princeton, NJ, USA Abstract In this chapter, we present the constrained MSL to exploit correlations learned from the training…
and Dorin Comaniciu1 (1) Imaging and Computer Vision, Siemens Corporate Technology, Princeton, NJ, USA Abstract The last decade saw tremendous advances in all major medical imaging modalities, with significant improvement…
and Dorin Comaniciu1 (1) Imaging and Computer Vision, Siemens Corporate Technology, Princeton, NJ, USA Abstract In this chapter, we adapt the Marginal Space Learning to the Left Ventricle (LV) detection…
and Dorin Comaniciu1 (1) Imaging and Computer Vision, Siemens Corporate Technology, Princeton, NJ, USA Abstract This book is centered around the efficient detection and segmentation of 2D and 3D anatomical…
