Mutual information based respiration detection

Martin-Leung, Barbara; Eck, Kai; Stuke, Ingo; Bredno, Joerg; Aach, Til

doi:10.1016/s0531-5131(03)00265-6

Cited by 8 publications

(9 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The method is not very robust and has not been shown to work with real datasets. In [8], the authors propose to detect the respiration (phase) using mutual information. The mutual information (MI) is calculated between the fluoroscopic image and a reference angiogram.…”

Section: Introductionmentioning

confidence: 99%

Automatic Image-Based Cardiac and Respiratory Cycle Synchronization and Gating of Image Sequences

Sundar

Khamene

Yatziv

et al. 2009

Medical Image Computing and Computer-Assisted Intervention – MICCAI 2009

View full text Add to dashboard Cite

Abstract. We propose a novel method to detect the current state of the quasi-periodic system from image sequences which in turn will enable us to synchronize/gate the image sequences to obtain images of the organ system at similar configurations. The method uses the cumulated phase shift in the spectral domain of successive image frames as a measure of the net motion of objects in the scene. The proposed method is applicable to 2D and 3D time varying sequences and is not specific to the imaging modality. We demonstrate its effectiveness on X-Ray Angiographic and Cardiac and Liver Ultrasound sequences. Knowledge of the current (cardiac or respiratory) phase of the system, opens up the possibility for a purely image based cardiac and respiratory gating scheme for interventional and radiotherapy procedures.

show abstract

Section: Introductionmentioning

confidence: 99%

Automatic Image-Based Cardiac and Respiratory Cycle Synchronization and Gating of Image Sequences

Sundar

Khamene

Yatziv

et al. 2009

Medical Image Computing and Computer-Assisted Intervention – MICCAI 2009

View full text Add to dashboard Cite

show abstract

“…stenting after dilation). 1 The accurate fusing of this information requires a precise matching of the respiration and contraction status of these two sources of information. In addition, artefacts like patient movement have to be detected and compensated.…”

Section: Introductionmentioning

confidence: 99%

“…In this context, heartbeat-and respiration sensing algorithms have been developed and presented earlier. 2,1 Also, a software architecture suitable to quickly draw the best matching mask from a number of mask images is presented. 3 The combination of these results allowed us to build a stroboscopic updating navigation aid prototype, which is currently under clinical testing.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Synthesis of angiographic images using iterative approximation

2004

Self Cite

View full text Add to dashboard Cite

In coronary x-ray angiographies, the vessels supplying the heart are imaged in a number of states uniquely determined by a combination of the respiratory intake and the heart contraction of the patient. The angiographic frames of one sequence represent not all possible combinations of respiration and heart contraction. A couple of applications need a continuous and dense sampling of the state-space given by the two axes 'respiration' and 'contraction', e.g. background removal or motion-compensated catheter navigation. We present a novel method of interpolating above the twodimensional phase-space based on pairs of angiographic frames with similar contraction, but different respiration status. First a hypothetical model of the respiration motion is formulated, e.g. rigid transformation or rigid translation. Then the parameters that transform a single frame into another one with similar contraction status are calculated for a number of frames. An iterative approach is used to reconstruct the generalized transformation function from the transformation parameters of frame pairs. Using this function, angiographic frames of arbitrary respiration status can be generated. It is shown that the synthesized angiographies closely match real angiographies acquired at the same combination of contraction and respiration status.

show abstract

“…To analyze the myocardial blush during its entire duration, the images showing insufficient contrast are matched with respect to heart phase and breathing status of the patient as described in Refs. [4], [5] and [8] to the contrasted images which are acquired during the complete state. The ROI is then projected from the contrasted to the non-contrasted images.…”

Section: Methodsmentioning

confidence: 99%