{"ID":2881660,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2508.12023","arxiv_id":"2508.12023","title":"WiseLVAM: A Novel Framework For Left Ventricle Automatic Measurements","abstract":"Clinical guidelines recommend performing left ventricular (LV) linear measurements in B-mode echocardiographic images at the basal level -- typically at the mitral valve leaflet tips -- and aligned perpendicular to the LV long axis along a virtual scanline (SL). However, most automated methods estimate landmarks directly from B-mode images for the measurement task, where even small shifts in predicted points along the LV walls can lead to significant measurement errors, reducing their clinical reliability. A recent semi-automatic method, EnLVAM, addresses this limitation by constraining landmark prediction to a clinician-defined SL and training on generated Anatomical Motion Mode (AMM) images to predict LV landmarks along the same. To enable full automation, a contour-aware SL placement approach is proposed in this work, in which the LV contour is estimated using a weakly supervised B-mode landmark detector. SL placement is then performed by inferring the LV long axis and the basal level- mimicking clinical guidelines. Building on this foundation, we introduce \\textit{WiseLVAM} -- a novel, fully automated yet manually adaptable framework for automatically placing the SL and then automatically performing the LV linear measurements in the AMM mode. \\textit{WiseLVAM} utilizes the structure-awareness from B-mode images and the motion-awareness from AMM mode to enhance robustness and accuracy with the potential to provide a practical solution for the routine clinical application. The source code is publicly available at https://github.com/SFI-Visual-Intelligence/wiselvam.git.","short_abstract":"Clinical guidelines recommend performing left ventricular (LV) linear measurements in B-mode echocardiographic images at the basal level -- typically at the mitral valve leaflet tips -- and aligned perpendicular to the LV long axis along a virtual scanline (SL). However, most automated methods estimate landmarks direct...","url_abs":"https://arxiv.org/abs/2508.12023","url_pdf":"https://arxiv.org/pdf/2508.12023v2","authors":"[\"Durgesh Kumar Singh\",\"Qing Cao\",\"Sarina Thomas\",\"Ahcène Boubekki\",\"Robert Jenssen\",\"Michael Kampffmeyer\"]","published":"2025-08-16T11:58:01Z","proceeding":"cs.CV","tasks":"[\"cs.CV\"]","methods":"[]","has_code":false,"code_links":[{"ID":610832,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_id":2881660,"paper_url":"https://arxiv.org/abs/2508.12023","paper_title":"WiseLVAM: A Novel Framework For Left Ventricle Automatic Measurements","repo_url":"https://github.com/SFI-Visual-Intelligence/wiselvam.git","is_official":false,"mentioned_in_paper":false,"mentioned_in_github":true,"github_stars":0}]}