Results 131 to 140 of about 170,175 (308)
Learning shape statistics for hierarchical 3D medical image segmentation [PDF]
, 2011 Accurate image segmentation is important for many medical imaging applications, whereas it remains challenging due to the complexity in medical images, such as the complex shapes and varied neighbor structures.
YuanYuan +4 more
core
Open-source software platform for medical image segmentation applications [PDF]
, 2017 Segmenting 2D and 3D images is a crucial and challenging problem in medical image analysis. Although several image segmentation algorithms have been proposed for different applications, no universal method currently exists. Moreover, their use is usually
Rafael Namias +5 more
core +1 more source
Astrocyte heterogeneity in brain metastases
Molecular Oncology, EarlyView.Astrocytes emerge as pivotal regulators of metastatic colonization, survival, immune remodeling, and therapy response associated with an increasing heterogeneity that requires spatially and longitudinally resolved approaches to uncover regulatory programs and guide context‐specific therapies.
Carolina Hernández‐Oliver +2 more
wiley +1 more source
Molecular Oncology, EarlyView.Detecting circulating tumor cells (CTCs) in blood before surgery may help predict outcomes in patients with head and neck squamous cell carcinoma (HNSCC). Here, we show when combined with tumor size and lymph node involvement from routine imaging, CTC status identifies high‐risk patients with poorer survival—offering a simple, minimally invasive tool ...
Susanne Flach +9 more
wiley +1 more source
A semi-supervised map segmentation of brain tissues [PDF]
, 2004 This paper presents a method for semi-supervised MAP (maximum a-posterior probability) segmentation of brain tissues where labelled data are available for either all types of tissues or only a few types of tissues possibly at different levels of quality.
de Silva, C., Li, W., Attikiouzel, Y.
core +1 more source
Molecular Oncology, EarlyView.Single‐cell DNA methylation (scDNAme) profiling maps epimutational clonal evolution, revealing mechanisms of malignancy and therapeutic resistance across diverse cancer types. By providing a high‐resolution landscape of intratumoral heterogeneity, these technologies empower precise patient stratification, guide the development of enhanced ...
Ik Soo Kim
wiley +1 more source
Image and Volume Segmentation by Water Flow [PDF]
, 2007 A general framework for image segmentation is presented in this paper, based on the paradigm of water flow. The major water flow attributes like water pressure, surface tension and capillary force are defined in the context of force field generation and ...
Liu, Xin U., Nixon, Mark S.
core
DB-SAM: Delving into High Quality Universal Medical Image Segmentation [PDF]
Recently, the Segment Anything Model (SAM) has demonstrated promising segmentation capabilities in a variety of downstream segmentation tasks. However in the context of universal medical image segmentation there exists a notable performance discrepancy ...
Qin, Chao, +4 more
core +1 more source
FEBS Open Bio, EarlyView.RoboMic is an automated confocal microscopy pipeline for high‐throughput functional imaging in living cells. Demonstrated with fluorescence recovery after photobleaching (FRAP), it integrates AI‐driven nuclear segmentation, ROI selection, bleaching, and analysis.
Selçuk Yavuz +6 more
wiley +1 more source
Raman‐based label‐free microscopic analysis of the pancreas in living zebrafish larvae
FEBS Open Bio, EarlyView.Forward stimulated Raman scattering (F‐SRS) and epi coherent anti‐Stokes Raman scattering (E‐CARS) allow label‐free discrimination of distinct subcellular structures in the pancreas of living zebrafish larvae. Given the straightforward applicability, we anticipate broad implementation of Raman microscopy in other organs and across various biomedical ...
Noura Faraj +3 more
wiley +1 more source