2016年3月15日 · PDDCA version 1.4.1 comprises 48 patient CT images from the Radiation Therapy Oncology Group (RTOG) 0522 study (a multi-institutional clinical trial led by Dr Kian Ang), together with manual segmentation of left and right parotid glands, brainstem, optic chiasm, optic nerves (both left and right), mandible, submandibular glands (both left and ri...

PDDCA 是一个分割任务的CT数据集，来自放射治疗肿瘤学研究组（RTOG）0522研究（由Kian Ang博士领导的多机构临床试验）的 48 例患者CT图像，以及左、右腮腺、脑干、视交叉、视神经（左右两侧）、下颌骨、颌下腺（左右两侧）的手动分割以及骨标记的手动标识。 该数据集也曾用于 MICCAI Head and Neck Auto Segmentation Challenge 2015 的挑战赛，官方将数据集划分为 38 个训练样本和 10 个测试样本。 PDDCA 数据集持续更新，当前最新版本为1.4.1.

PDDCA is a CT dataset for segmentation tasks, derived from the CT images of 48 patients from the Radiation Therapy Oncology Group (RTOG) 0522 study (a multi-institutional clinical trial led by Dr. Kian Ang), which includes manual segmentations of the left and right parotid glands, brainstem, optic chiasm, optic nerves (left and right sides), man...

PDDCA version 1.4.1 comprises 48 patient CT images from the Radiation Therapy Oncology Group (RTOG) 0522 study (a multi-institutional clinical trial led by Dr Kian Ang), together with manual segmentation of left and right parotid glands, brainstem, optic chiasm, optic nerves (both left and right), mandible, submandibular glands (both left and ri...

In the following examples, we use the PDDCA dataset, and name it as data. The structure of PDDCA dataset is like the following and in NRRD data format (.nrrd). We have written a parser named PDDCA parser for this dataset. One can directly use parser to serve the data loading or convert the source data to a consistent format.

Github 版本: openmedlab/Awesome-Medical-Dataset: Collection of awesome medical dataset resources.影像数据集 (365)全身（12） TotalSegmentator (3D CT, 1204例, 104类全身器官分割) TotalSegmentator v2 (3…

PDDCA 版本 1.4.1 包含来自放射治疗肿瘤组 (RTOG) 0522 研究（由 Kian Ang 博士领导的多机构临床试验）的 48 位患者 CT 图像，以及左右腮腺、脑干、视交叉的手动分割 ，视神经（左右），下颌骨，下颌下腺（左右）和骨性标志的人工识别。 我们将这些数据提供给社区，希望它能有所帮助。 描述和标记中的任何错误都是我们的，而不是参与医生的错。 请参阅 pddca.odt 以获取完整信息。 出于实际原因，数据库分为 3 个压缩文件。 第 3 部分包含缺少上面列出的某些结 …

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2021年4月15日 · In this paper, we propose a novel, automatic multiorgan segmentation algorithm based on a new hybrid neural-like P system, to alleviate the above challenges. The new P system possesses the joint advantages of cell-like and neural-like P systems and includes new structures and rules, allowing it to solve more real-world problems in parallelism.

Table 1. Dice score of validation on PDDCA dataset (train/valid: 33/15) ROI. Brainstem. Left Parotid. Right Parotid. Average. Score. 0.86830. 0.75442. 0.75059