Using the PDDCA dataset Dr. Kanglin Chen (Fraunhofer Institute for Medical Image Computing MEVIS) has built the probabilistic atlas linked below. The atlas, in addition to the mean anatomical volume, includes also the geometrical transformations, five bone landmarks and the probability maps of left/right parotids and of the brainstem.

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 …

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 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...

Quality Glossary Definition: Plan-do-check-act (PDCA) cycle. Variations: plan-do-study-act (PDSA) cycle, Deming cycle, Shewhart cycle. Understand the evolution of these variations. The Plan-do-check-act cycle (Figure 1) is a four-step model for carrying out change.

Sophisticated segmentation of the craniomaxillofacial bones (the mandible and maxilla) in computed tomography (CT) is essential for diagnosis and treatment planning for craniomaxillofacial...

Note that this script is for inference only. Hence, no label information required. But if you have label of images and want to evaluate the performance, or further training based on the model, please see here. 1. Latest results. Table 1. Dice score of validation on PDDCA dataset (train/valid: 33/15) 2. How to use. 2.1. Prerequisites.

PDCA or plan–do–check–act (sometimes called plan–do–check–adjust) is an iterative design and management method used in business for the control and continual improvement of processes and products. [1] . It is also known as the Shewhart cycle, or the control circle / cycle. Another version of this PDCA cycle is OPDCA. [2] .

Use PDDCA18 (MICCAI) training + HNPETCT + HNCetuximab as training set. Use PDDCA18 test as test. The data spliting is in https://www.google.com/search?q=PDDCA+dataset&oq=PDDCA+dataset&aqs=chrome..69i57j0l5.3910j0j7&sourceid=chrome&ie=UTF-8. ./data/*.csv files are used to remove non-head and neck regions.

For correlated landmarks, we mimic the manual annotation process and propose a correlated landmark detection model that merges information from various patches to query key slices and identify correlated landmarks.