776c6e8a137821a33038064785cacedb diagnostics_13_00910_v2.pdf 5dca62688c83e9f9636f67b8b8f1f00e38d51ea1 diagnostics_13_00910_v2.pdf 4c2fd6f7bf6946f1e8e6361d6f2359effcd6c842b99a583a5e1eeb609acf82e0 diagnostics_13_00910_v2.pdf Title: End to End Colonic Content Assessment: ColonMetry Application Subject: The analysis of colonic contents is a valuable tool for the gastroenterologist and has multiple applications in clinical routine. When considering magnetic resonance imaging (MRI) modalities, T2 weighted images are capable of segmenting the colonic lumen, whereas fecal and gas contents can only be distinguished in T1 weighted images. In this paper, we present an end-to-end quasi-automatic framework that comprises all the steps needed to accurately segment the colon in T2 and T1 images and to extract colonic content and morphology data to provide the quantification of colonic content and morphology data. As a consequence, physicians have gained new insights into the effects of diets and the mechanisms of abdominal distension. Keywords: magnetic resonance imaging; colonic content; colon segmentation; intestinal biomass; intestinal gas; functional digestive disorders Author: Bernat Orellana, Eva Monclús, Isabel Navazo, Álvaro Bendezú, Carolina Malagelada and Fernando Azpiroz Creator: LaTeX with hyperref Producer: pdfTeX-1.40.21 CreationDate: Wed Mar 1 10:44:19 2023 CET ModDate: Wed Mar 1 10:56:13 2023 CET Tagged: no UserProperties: no Suspects: no Form: none JavaScript: no Pages: 10 Encrypted: no Page size: 595.276 x 841.89 pts (A4) Page rot: 0 File size: 5506623 bytes Optimized: no PDF version: 1.7 name type encoding emb sub uni object ID ------------------------------------ ----------------- ---------------- --- --- --- --------- IGBEBF+VnURWPalladioL-Bold Type 1 Custom yes yes no 10 0 RAFMMA+VnURWPalladioL Type 1 Custom yes yes no 15 0 BGCLVN+URWPalladioL-Bold Type 1 Custom yes yes no 19 0 HBASXZ+URWPalladioL-Roma Type 1 Custom yes yes no 24 0 SYXHOM+URWPalladioL-Ital Type 1 Custom yes yes no 28 0 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(2019-04-17) LastModified: 2023-05-10 01:34:19 CEST Size: 5506623 Format: PDF Version: 1.7 Status: Well-Formed and valid SignatureMatches: PDF-hul MIMEtype: application/pdf PDFMetadata: Objects: 350 FreeObjects: 1 IncrementalUpdates: 0 DocumentCatalog: PageLayout: SinglePage PageMode: UseNone Outlines: Item: Title: Introduction Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@44c8afef Item: Title: Materials and Methods Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@7b69c6ba Children: Item: Title: Colon Segmentation in T2 Images Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@46daef40 Item: Title: Colon Segmentation in T1-FS Images Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@12f41634 Item: Title: Synchronized T2 and T1-FS Inspection Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@13c27452 Item: Title: Colon Content Analysis Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@262b2c86 Item: Title: Acquisition Protocol Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@371a67ec Item: Title: Results Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@5ed828d Children: Item: Title: Validation of the Colon Segmentation from T2 and T1-FS Images Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@50d0686 Item: Title: Validation of the Synchronized Navigation in T2 and T1-FS Images Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@7a3d45bd Item: Title: Discussion Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@1e7c7811 Item: Title: References Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@77ec78b9 Info: Title: End to End Colonic Content Assessment: ColonMetry Application Author: Bernat Orellana, Eva Monclús, Isabel Navazo, Álvaro Bendezú, Carolina Malagelada and Fernando Azpiroz Subject: The analysis of colonic contents is a valuable tool for the gastroenterologist and has multiple applications in clinical routine. When considering magnetic resonance imaging (MRI) modalities, T2 weighted images are capable of segmenting the colonic lumen, whereas fecal and gas contents can only be distinguished in T1 weighted images. In this paper, we present an end-to-end quasi-automatic framework that comprises all the steps needed to accurately segment the colon in T2 and T1 images and to extract colonic content and morphology data to provide the quantification of colonic content and morphology data. As a consequence, physicians have gained new insights into the effects of diets and the mechanisms of abdominal distension. 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