000			01989nam a2200373Ia 4500
000			05527nam a22003975i 4500
001			978-3-031-27420-6
003			DE-He213
005			20240319120844.0
007			cr nn 008mamaa
008			230317s2023 sz | s |||| 0|eng d
020			_a9783031274206 _9978-3-031-27420-6
082			_a6
245			_aHead and Neck Tumor Segmentation and Outcome Prediction _cedited by Vincent Andrearczyk, Valentin Oreiller, Mathieu Hatt, Adrien Depeursinge. _h[electronic resource] :
250			_a1st ed. 2023.
260			_aCham _bSpringer Nature Switzerland _c2023
300			_aXI, 257 p. 75 illus., 67 illus. in color. _bonline resource.
520			_aThis book constitutes the Third 3D Head and Neck Tumor Segmentation in PET/CT Challenge, HECKTOR 2022, which was held in conjunction with the 25th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2022, on September 22, 2022. The 22 contributions presented, as well as an overview paper, were carefully reviewed and selected from 24 submissions. This challenge aims to evaluate and compare the current state-of-the-art methods for automatic head and neck tumor segmentation. In the context of this challenge, a dataset of 883 delineated PET/CT images was made available for training. .
650			_aBioinformatics. _930698
650			_aComputational and Systems Biology. _930699
650			_aComputer Imaging, Vision, Pattern Recognition and Graphics. _930700
650			_aComputer vision. _930701
650			_aImage processing _930702
650			_aImage processing. _930702
650			_aImage Processing. _930703
650			_aMachine learning. _930704
650			_aMachine Learning. _930705
700			_aAndrearczyk, Vincent. _930706
700			_aDepeursinge, Adrien. _930707
700			_aHatt, Mathieu. _930708
700			_aOreiller, Valentin. _930709
856			_uhttps://doi.org/10.1007/978-3-031-27420-6
942			_cEBK _2ddc
999			_c15152 _d15152