Landmark detection with spatial and temporal constraints in medical imaging

Anatomy, such as papillary muscle, is automatically detected (34) and/or detected in real-time. For automatic detection (34) of small anatomy, machine-learnt classification with spatial (32) and temporal (e.g., Markov) (34) constraints is used. For real-time detection, sparse machine-learnt detectio...

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Bibliographic Details
Main Authors IONASEC RAZVAN, MANSI TOMMASO, VOIGT INGMAR, GEORGESCU BOGDAN, SCUTARU MIHAI, EL-ZEHIRY NOHA YOUSSRY, HOULE HELENE C, TATPATI ANAND VINOD, COMANICIU DORIN
Format Patent
LanguageChinese
English
Published 26.04.2017
Subjects
CALCULATING
COMPUTING
COUNTING
IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
PHYSICS
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Summary:Anatomy, such as papillary muscle, is automatically detected (34) and/or detected in real-time. For automatic detection (34) of small anatomy, machine-learnt classification with spatial (32) and temporal (e.g., Markov) (34) constraints is used. For real-time detection, sparse machine-learnt detection (34) interleaved with optical flow tracking (38) is used. 自动检测（34）和/或实时检测诸如乳头肌的解剖结构。对于小解剖结构的自动检测（34），使用具有空间约束（32）和时间（例如，马尔可夫）约束（34）的机器学习分类。对于实时检测，使用与光流跟踪（38）交错的稀疏机器学习检测（34）。
Bibliography:Application Number: CN201580030902