Results 51 to 60 of about 4,638,101 (75)

Hyper-Pairing Network for Multi-Phase Pancreatic Ductal Adenocarcinoma Segmentation [PDF]

open access: yesarXiv, 2019
Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancers with an overall five-year survival rate of 8%. Due to subtle texture changes of PDAC, pancreatic dual-phase imaging is recommended for better diagnosis of pancreatic disease. In this study, we aim at enhancing PDAC automatic segmentation by integrating multi-phase information (i ...
arxiv  

Pancreatic Tumor Segmentation as Anomaly Detection in CT Images Using Denoising Diffusion Models [PDF]

open access: yesarXiv
Despite the advances in medicine, cancer has remained a formidable challenge. Particularly in the case of pancreatic tumors, characterized by their diversity and late diagnosis, early detection poses a significant challenge crucial for effective treatment.
arxiv  

Cross-Organ Domain Adaptive Neural Network for Pancreatic Endoscopic Ultrasound Image Segmentation [PDF]

open access: yesarXiv
Accurate segmentation of lesions in pancreatic endoscopic ultrasound (EUS) images is crucial for effective diagnosis and treatment. However, the collection of enough crisp EUS images for effective diagnosis is arduous. Recently, domain adaptation (DA) has been employed to address these challenges by leveraging related knowledge from other domains. Most
arxiv  

Optimizing Synthetic Data for Enhanced Pancreatic Tumor Segmentation [PDF]

open access: yesarXiv
Pancreatic cancer remains one of the leading causes of cancer-related mortality worldwide. Precise segmentation of pancreatic tumors from medical images is a bottleneck for effective clinical decision-making. However, achieving a high accuracy is often limited by the small size and availability of real patient data for training deep learning models ...
arxiv  

Enhancing Pancreatic Cancer Staging with Large Language Models: The Role of Retrieval-Augmented Generation [PDF]

open access: yesarXiv
Purpose: Retrieval-augmented generation (RAG) is a technology to enhance the functionality and reliability of large language models (LLMs) by retrieving relevant information from reliable external knowledge (REK). RAG has gained interest in radiology, and we previously reported the utility of NotebookLM, an LLM with RAG (RAG-LLM), for lung cancer ...
arxiv  

Opportunistic Screening for Pancreatic Cancer using Computed Tomography Imaging and Radiology Reports [PDF]

open access: yesarXiv
Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive cancer, with most cases diagnosed at stage IV and a five-year overall survival rate below 5%. Early detection and prognosis modeling are crucial for improving patient outcomes and guiding early intervention strategies.
arxiv  

The tumour microenvironment in pancreatic cancer — clinical challenges and opportunities

open access: yesNature Reviews Clinical Oncology, 2020
W. J. Ho, E. Jaffee, Lei Zheng
semanticscholar   +1 more source

Pancreatic cancer stroma: an update on therapeutic targeting strategies

open access: yesNature reviews: Gastroenterology & hepatology, 2020
A. Hosein, R. Brekken, A. Maitra
semanticscholar   +1 more source

Whole genomes redefine the mutational landscape of pancreatic cancer

open access: yesNature, 2015
N. Waddell   +88 more
semanticscholar   +1 more source

Glypican-1 identifies cancer exosomes and detects early pancreatic cancer

open access: yesNature, 2015
S. Melo   +14 more
semanticscholar   +1 more source

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