{"id":409405,"date":"2024-10-20T05:35:22","date_gmt":"2024-10-20T05:35:22","guid":{"rendered":"https:\/\/pdfstandards.shop\/product\/uncategorized\/bsi-22-30426016-dc\/"},"modified":"2024-10-26T10:14:54","modified_gmt":"2024-10-26T10:14:54","slug":"bsi-22-30426016-dc","status":"publish","type":"product","link":"https:\/\/pdfstandards.shop\/product\/publishers\/bsi\/bsi-22-30426016-dc\/","title":{"rendered":"BSI 22\/30426016 DC"},"content":{"rendered":"
PDF Pages<\/th>\n | PDF Title<\/th>\n<\/tr>\n | ||||||
---|---|---|---|---|---|---|---|
7<\/td>\n | Foreword <\/td>\n<\/tr>\n | ||||||
8<\/td>\n | Introduction <\/td>\n<\/tr>\n | ||||||
9<\/td>\n | 1 Scope 2 Normative references 3 Terms and definitions <\/td>\n<\/tr>\n | ||||||
10<\/td>\n | 4 Abbreviations <\/td>\n<\/tr>\n | ||||||
11<\/td>\n | 5 Objective of segmentation 5.1 Background 5.2 Related works <\/td>\n<\/tr>\n | ||||||
12<\/td>\n | 6 Overall segmentation process 6.1 General 6.2 Step1: data preparation <\/td>\n<\/tr>\n | ||||||
13<\/td>\n | 6.3 Step2: preprocessing for segmentation 6.4 Step3: annotation 6.5 Step4: selection of segmentation network model 6.6 Step5: performance evaluation 6.7 Step6: model deployment and running 6.8 Step7: post-processing for segmentation 7 Data preparation 7.1 General 7.2 Medical image 7.2.1 General 7.2.2 CT scan <\/td>\n<\/tr>\n | ||||||
14<\/td>\n | 7.2.3 MRI scan 7.3 Preparation steps 7.3.1 General 7.3.2 Image acquisition 7.3.3 Image reconstruction 8 Preprocessing for segmentation 8.1 General <\/td>\n<\/tr>\n | ||||||
15<\/td>\n | 8.2 Intensity normalization 8.3 Spacing normalization <\/td>\n<\/tr>\n | ||||||
16<\/td>\n | 9 Annotation 9.1 Data labeling 9.2 Pre-processing for annotation 9.3 Dataset management (training and testing) <\/td>\n<\/tr>\n | ||||||
17<\/td>\n | 9.4 Augmentation 10 Selection of network model 10.1 General <\/td>\n<\/tr>\n | ||||||
18<\/td>\n | 10.2 Input patch 11 Evaluation 11.1 General <\/td>\n<\/tr>\n | ||||||
19<\/td>\n | 11.2 Evaluation metrics 11.3 Evaluation procedure <\/td>\n<\/tr>\n | ||||||
20<\/td>\n | 12 Deployment and running 13 Post-processing for segmentation <\/td>\n<\/tr>\n | ||||||
21<\/td>\n | Annex\u20acA (informative) CT scanning conditions for orbital bone segmentation <\/td>\n<\/tr>\n | ||||||
22<\/td>\n | Annex\u20acB (informative) Characteristics of orbital bone segmentation from CT <\/td>\n<\/tr>\n | ||||||
25<\/td>\n | Annex\u20acC (informative) Deep learning techniques <\/td>\n<\/tr>\n | ||||||
26<\/td>\n | Annex\u20acD (informative) Considerations for overall segmentation performance <\/td>\n<\/tr>\n | ||||||
31<\/td>\n | Bibliography <\/td>\n<\/tr>\n<\/table>\n","protected":false},"excerpt":{"rendered":" BS ISO\/IEC 3532-2. Information technology. 3D Printing and scanning. Medical image-Based modelling – Part 2: Segmentation<\/b><\/p>\n |