ArticlePatch-based techniques in medical imaging : 4th international workshop, Patch-MI 2018, held in conjunction with MICCAI 2018, Granada, Spain, September 20, 2018 : proceedings. Patch-MI (Workshop) (4th : 2018 : Granada, Spain)2018
Multi-atlas Parcellation in the Presence of Lesions: Application to Multiple Sclerosis.
Article in Patch-based techniques in medical imaging : 4th international workshop, Patch-MI 2018, held in conjunction with MICCAI 2018, Granada, Spain, September 20, 2018 : proceedings. Patch-MI (Workshop) (4th : 2018 : Granada, Spain), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
2 citing papers in PubMed.
- A joint ventricle and WMH segmentation from MRI for evaluation of healthy and pathological changes in the aging brain.PloS one · 2022Article
- Brain structure segmentation in the presence of multiple sclerosis lesions.NeuroImage. Clinical · 2019Article
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5 authors.
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Abstract
Intensity-based multi-atlas strategies have shown leading performance in segmenting healthy subjects, but when lesions are present, the abnormal lesion intensities affect the fusion result. Here, we propose a reformulated statistical fusion approach for multi-atlas segmentation that is applicable to both healthy and injured brains. This method avoids the interference of lesion intensities on the segmentation by incorporating two
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.