Segmentation-Driven Image Registration-Application to 4D DCE-MRI Recordings of the Moving Kidneys

Hodneland, Erlend; Hanson, Erik Andreas; Lundervold, Arvid; Modersitzki, Jan; Eikefjord, Eli; Munthe-Kaas, Antonella Zanna

doi:10.1109/tip.2014.2315155

Cited by 30 publications

(27 citation statements)

References 51 publications

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“…Image registration methods are particularly important in radiation therapy and volumetric imaging (16)(17)(18). One of the major applications is TS; however, to our knowledge, this technique has not been put into practical use for clinical CT images, even for the skeletal structure, although it consists small osteolytic lesions, without apparent destruction of the bony cortex.…”

Section: Discussionmentioning

confidence: 99%

Temporal Subtraction of Serial CT Images with Large Deformation Diffeomorphic Metric Mapping in the Identification of Bone Metastases

et al. 2017

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Purpose To determine the improvement of radiologist efficiency and performance in the detection of bone metastases at serial follow-up computed tomography (CT) by using a temporal subtraction (TS) technique based on an advanced nonrigid image registration algorithm. Materials and Methods This retrospective study was approved by the institutional review board, and informed consent was waived. CT image pairs (previous and current scans of the torso) in 60 patients with cancer (primary lesion location: prostate, n = 14; breast, n = 16; lung, n = 20; liver, n = 10) were included. These consisted of 30 positive cases with a total of 65 bone metastases depicted only on current images and confirmed by two radiologists who had access to additional imaging examinations and clinical courses and 30 matched negative control cases (no bone metastases). Previous CT images were semiautomatically registered to current CT images by the algorithm, and TS images were created. Seven radiologists independently interpreted CT image pairs to identify newly developed bone metastases without and with TS images with an interval of at least 30 days. Jackknife free-response receiver operating characteristics (JAFROC) analysis was conducted to assess observer performance. Reading time was recorded, and usefulness was evaluated with subjective scores of 1-5, with 5 being extremely useful and 1 being useless. Significance of these values was tested with the Wilcoxon signed-rank test. Results The subtraction images depicted various types of bone metastases (osteolytic, n = 28; osteoblastic, n = 26; mixed osteolytic and blastic, n = 11) as temporal changes. The average reading time was significantly reduced (384.3 vs 286.8 seconds; Wilcoxon signed rank test, P = .028). The average figure-of-merit value increased from 0.758 to 0.835; however, this difference was not significant (JAFROC analysis, P = .092). The subjective usefulness survey response showed a median score of 5 for use of the technique (range, 3-5). Conclusion TS images obtained from serial CT scans using nonrigid registration successfully depicted newly developed bone metastases and showed promise for their efficient detection. RSNA, 2017 Online supplemental material is available for this article.

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Section: Discussionmentioning

confidence: 99%

Temporal Subtraction of Serial CT Images with Large Deformation Diffeomorphic Metric Mapping in the Identification of Bone Metastases

et al. 2017

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“…Hodneland et al introduced a 4D model to improve the overall performance of the GFR evaluation by simultaneous registration and segmentation. Registration and segmentation are substantially different steps, but their combination can limit errors propagation through an appropriated feeding back of alignment of timepoints from one step to the next . In addition, registration is a necessary step to correct the effect of kidney motion, and nonrigid registration is more accurate.…”

Section: Renal Fmrimentioning

confidence: 99%

Renal Functional MRI and Its Application

Zhou

Wang

Zeng

et al. 2018

Magnetic Resonance Imaging

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“…The GFR might be determined on the basis of a time series of dynamic contrast-enhanced magnetic resonance images (DCE-MRI). This sequence then needs to be registered in order to correct for motion artifacts; see, e.g., [7,9]. Another example is the analysis of a histological serial sectioning.…”

Section: Introductionmentioning

confidence: 99%

A Novel Similarity Measure for Image Sequences

Brehmer

Wacker

Modersitzki

2018

Biomedical Image Registration

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Quantification of image similarity is a common problem in image processing. For pairs of two images, a variety of options is available and well-understood. However, some applications such as dynamic imaging or serial sectioning involve the analysis of image sequences and thus require a simultaneous and unbiased comparison of many images. This paper proposes a new similarity measure, that takes a global perspective and involves all images at the same time. The key idea is to look at Schatten-q-norms of a matrix assembled from normalized gradient fields of the image sequence. In particular, for q = 0, the measure is minimized if the gradient information from the image sequence has a low rank. This global perspective of the novel SqN-measure does not only allow to register sequences from dynamic imaging, e.g. DCE-MRI, but is also a new opportunity to simultaneously register serial sections, e.g. in histology. In this way, an accumulation of small, local registration errors may be avoided. First numerical experiments show very promising results for a DCE-MRI sequence of a human kidney as well as for a set of serial sections. The global structure of the data used for registration with SqN is preserved in all cases.

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Segmentation-Driven Image Registration-Application to 4D DCE-MRI Recordings of the Moving Kidneys

Cited by 30 publications

References 51 publications

Temporal Subtraction of Serial CT Images with Large Deformation Diffeomorphic Metric Mapping in the Identification of Bone Metastases

Temporal Subtraction of Serial CT Images with Large Deformation Diffeomorphic Metric Mapping in the Identification of Bone Metastases

Renal Functional MRI and Its Application

A Novel Similarity Measure for Image Sequences

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