Results 161 to 170 of about 5,905,711 (364)
Deep Learning in Medical Image Classification from MRI-based Brain Tumor Images [PDF]
arXivBrain tumors are among the deadliest diseases in the world. Magnetic Resonance Imaging (MRI) is one of the most effective ways to detect brain tumors. Accurate detection of brain tumors based on MRI scans is critical, as it can potentially save many lives and facilitate better decision-making at the early stages of the disease.
arxiv
Genomic landscape and preclinical models of angiosarcoma
Molecular Oncology, EarlyView.Angiosarcomas are a rare and aggressive cancer with a poor prognosis for patients. The genomic landscape of angiosarcoma can be highly complex and heterogenous; however, recent studies have identified some common features especially within anatomic and molecular subgroups.
Annaleigh Benton +3 more
wiley +1 more source
Cryoablation and Immunotherapy: An Enthralling Synergy to Confront the Tumors
Frontiers in Immunology, 2019 Treatment of solid tumors by ablation techniques has gained momentum in the recent years due to their technical simplicity and reduced morbidity as juxtaposed to surgery.
Chakradhar Yakkala +5 more
doaj +1 more source
Estimating the age of renal tumors [PDF]
arXiv, 2012 We present a Bayesian method for estimating the age of a renal tumor given its size. We use a model of tumor growth based on published data from observations of untreated tumors. We find, for example, that the median age of a 5 cm tumor is 20 years, with interquartile range 16-23 and 90% confidence interval 11-30 years.
arxiv
Molecular Oncology, EarlyView.Adaptive ERK reactivation hinders FLT3 tyrosine kinase inhibitor (TKI) treatment in FLT3/ITD acute myeloid leukemia. Here, we report that FLT3 TKI treatment rapidly induces AXL expression and upregulation that is temporally associated with the adaptive ERK reactivation.
Tessa S. Seale +9 more
wiley +1 more source
Automatic Brain Tumor Detection and Segmentation Using U-Net Based Fully Convolutional Networks [PDF]
arXiv, 2017 A major challenge in brain tumor treatment planning and quantitative evaluation is determination of the tumor extent. The noninvasive magnetic resonance imaging (MRI) technique has emerged as a front-line diagnostic tool for brain tumors without ionizing radiation.
arxiv
Molecular Oncology, EarlyView.The authors analyzed the spatial distributions of gene and metabolite profiles in cervical cancer through spatial transcriptomic and spatially resolved metabolomic techniques. Pivotal genes and metabolites within these cases were then identified and validated.
Lixiu Xu +3 more
wiley +1 more source
EVALUATING THE THERAPEUTIC EFFICACY OF RESTORING WILD-TYPE P53 ACTIVITY IN P53-MUTANT TUMORS [PDF]
, 2017 The p53 transcription factor is the most frequently altered in human cancers usually via missense mutations that undermine its transcriptional activity. Clinically, TP53 mutations have been shown to be remarkably predictive of refractoriness to treatment,
Larsson, Connie A
core +1 more source
From Pixel to Cancer: Cellular Automata in Computed Tomography [PDF]
arXivAI for cancer detection encounters the bottleneck of data scarcity, annotation difficulty, and low prevalence of early tumors. Tumor synthesis seeks to create artificial tumors in medical images, which can greatly diversify the data and annotations for AI training.
arxiv
3D Kidneys and Kidney Tumor Semantic Segmentation using Boundary-Aware Networks [PDF]
MICCAI Kidney Tumor Segmentation Challenge 2019, 2019 Automated segmentation of kidneys and kidney tumors is an important step in quantifying the tumor's morphometrical details to monitor the progression of the disease and accurately compare decisions regarding the kidney tumor treatment. Manual delineation techniques are often tedious, error-prone and require expert knowledge for creating unambiguous ...
arxiv