Search Results for author: Daniel Razansky

Found 6 papers, 1 papers with code

Simulation-Based Segmentation of Blood Vessels in Cerebral 3D OCTA Images

no code implementations11 Mar 2024 Bastian Wittmann, Lukas Glandorf, Johannes C. Paetzold, Tamaz Amiranashvili, Thomas Wälchli, Daniel Razansky, Bjoern Menze

Segmentation of blood vessels in murine cerebral 3D OCTA images is foundational for in vivo quantitative analysis of the effects of neurovascular disorders, such as stroke or Alzheimer's, on the vascular network.

Segmentation

OADAT: Experimental and Synthetic Clinical Optoacoustic Data for Standardized Image Processing

1 code implementation17 Jun 2022 Firat Ozdemir, Berkan Lafci, Xosé Luís Deán-Ben, Daniel Razansky, Fernando Perez-Cruz

However, no standardized datasets generated with different types of experimental set-up and associated processing methods are available to facilitate advances in broader applications of OA in clinical settings.

Image Reconstruction Image-to-Image Translation +1

Deep learning facilitates fully automated brain image registration of optoacoustic tomography and magnetic resonance imaging

no code implementations4 Sep 2021 Yexing Hu, Berkan Lafci, Artur Luzgin, Hao Wang, Jan Klohs, Xose Luis Dean-Ben, Ruiqing Ni, Daniel Razansky, Wuwei Ren

Multi-spectral optoacoustic tomography (MSOT) is an emerging optical imaging method providing multiplex molecular and functional information from the rodent brain.

Anatomy Brain Segmentation +4

Maximum entropy based non-negative optoacoustic tomographic image reconstruction

no code implementations26 Jul 2017 Jaya Prakash, Subhamoy Mandal, Daniel Razansky, Vasilis Ntziachristos

The aim of the work is to develop an inversion method which reduces the occurrence of negative values and improves the quantitative performance of optoacoustic imaging.

Image Reconstruction

Visual Quality Enhancement in Optoacoustic Tomography using Active Contour Segmentation Priors

no code implementations28 Oct 2015 Subhamoy Mandal, Xosé Luís Deán-Ben, Daniel Razansky

Segmentation has been further shown to enhance the reconstruction performance in many tomographic imaging modalities by accounting for heterogeneities of the excitation field and tissue properties in the imaged region.

Image Reconstruction Segmentation

Multiscale edge detection and parametric shape modeling for boundary delineation in optoacoustic images

no code implementations9 Jun 2015 Subhamoy Mandal, Viswanath Pamulakanty Sudarshan, Yeshaswini Nagaraj, Xose Luis Dean Ben, Daniel Razansky

In this article, we present a novel scheme for segmenting the image boundary (with the background) in optoacoustic small animal in vivo imaging systems.

Edge Detection

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