Results 91 to 100 of about 56,273 (232)
LN-Gen: Rectal Lymph Nodes Generation via Anatomical Features [PDF]
Accurate segmentation of rectal lymph nodes is crucial for the staging and treatment planning of rectal cancer. However, the complexity of the surrounding anatomical structures and the scarcity of annotated data pose significant challenges. This study introduces a novel lymph node synthesis technique aimed at generating diverse and realistic synthetic ...
arxiv
The Application of Deep Learning for Lymph Node Segmentation: A Systematic Review [PDF]
Automatic lymph node segmentation is the cornerstone for advances in computer vision tasks for early detection and staging of cancer. Traditional segmentation methods are constrained by manual delineation and variability in operator proficiency, limiting their ability to achieve high accuracy.
arxiv
WeGA: Weakly-Supervised Global-Local Affinity Learning Framework for Lymph Node Metastasis Prediction in Rectal Cancer [PDF]
Accurate lymph node metastasis (LNM) assessment in rectal cancer is essential for treatment planning, yet current MRI-based evaluation shows unsatisfactory accuracy, leading to suboptimal clinical decisions. Developing automated systems also faces significant obstacles, primarily the lack of node-level annotations. Previous methods treat lymph nodes as
arxiv
735 HLA ANTIGENS IN MUCOCUTANEOUS LYMPH NODE SYNDROME (MLNS) [PDF]
Alan M. Krensky+4 more
openalex +1 more source
Enfermedad de Kawasaki. Aspectos a considerar Kawasaki disease. Aspects to take into consideration
La enfermedad de Kawasaki ha sido objeto de interés por epidemiólogos, clínicos e investigadores, desde su primera descripción en 1967. Su causa no se ha podido identificar, aunque las principales hipótesis apuntan a una etiología infecciosa.
Lázaro Arturo Vidal Tallet+5 more
doaj
Circulating immune complexes in mucocutaneous lymph-node syndrome (Kawasaki disease) [PDF]
A M Weindling+3 more
openalex +1 more source
Ultrastructure of the myocardium in acute febrile mucocutaneous lymph node syndrome.
Munehiko Tomisawa+6 more
openalex +2 more sources