Searching beyond the usual papillomavirus suspects in squamous carcinomas of the vulva, penis and head and neck [PDF]
Infection, Genetics and Evolution, Elsevier, 2016, 45, pp.198-204, 2020 Human Papillomaviruses (HPVs) are involved in the etiology of anogenital and head and neck cancers. The HPV DNA prevalence greatly differs by anatomical site. Indeed, the high rates of viral DNA prevalence in anal and cer-vical carcinomas contrast with the lower fraction of cancer cases attributable to HPVs in other anatomical sites, chiefly the vulva,
arxiv +1 more source
AI-based Carcinoma Detection and Classification Using Histopathological Images: A Systematic Review [PDF]
arXiv, 2022 Histopathological image analysis is the gold standard to diagnose cancer. Carcinoma is a subtype of cancer that constitutes more than 80% of all cancer cases. Squamous cell carcinoma and adenocarcinoma are two major subtypes of carcinoma, diagnosed by microscopic study of biopsy slides.
arxiv
Patch-based Carcinoma Detection on Confocal Laser Endomicroscopy Images -- A Cross-Site Robustness Assessment [PDF]
Proceedings of BIOIMAGING 2018, ISBN: 978-989-758-278-3, 2017 Deep learning technologies such as convolutional neural networks (CNN) provide powerful methods for image recognition and have recently been employed in the field of automated carcinoma detection in confocal laser endomicroscopy (CLE) images. CLE is a (sub-)surface microscopic imaging technique that reaches magnifications of up to 1000x and is thus ...
arxiv +1 more source
Air cold atmospheric plasma with patterns for anaplastic squamous cell carcinoma treatment [PDF]
arXiv, 2023 In recent years, cold atmospheric plasma (CAP) using inert gas has been successfully applied for biomedicine, such as sterilization, wound healing, skin diseases, and tumor treatment. Here, we reported air cold atmospheric plasma with three different patterns (I. Non: basic square grid structure; II.
arxiv
Uncertainty-Informed Deep Learning Models Enable High-Confidence Predictions for Digital Histopathology [PDF]
, 2022 A model's ability to express its own predictive uncertainty is an essential attribute for maintaining clinical user confidence as computational biomarkers are deployed into real-world medical settings. In the domain of cancer digital histopathology, we describe a novel, clinically-oriented approach to uncertainty quantification (UQ) for whole-slide ...
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Hematoxylin and eosin stained oral squamous cell carcinoma histological images dataset [PDF]
arXiv, 2023 Computer-aided diagnosis (CAD) can be used as an important tool to aid and enhance pathologists' diagnostic decision-making. Deep learning techniques, such as convolutional neural networks (CNN) and fully convolutional networks (FCN), have been successfully applied in medical and biological research.
arxiv
Prediction of post-radiotherapy recurrence volumes in head and neck squamous cell carcinoma using 3D U-Net segmentation [PDF]
arXiv, 2023 Locoregional recurrences (LRR) are still a frequent site of treatment failure for head and neck squamous cell carcinoma (HNSCC) patients. Identification of high risk subvolumes based on pretreatment imaging is key to biologically targeted radiation therapy.
arxiv
Survival prediction of head and neck squamous cell carcinoma using machine learning models [PDF]
arXiv, 2021 Head and Neck Squamous Cell Carcinoma (HNSCC) is one of cancer type that is most distressing leading to acute pain, effecting speech and primary survival functions such as swallowing and breathing. The morbidity and mortality of HNSCC patients have not significantly improved even tough there has been advancement in surgical and radiotherapy treatments.
arxiv
Interpretable Prediction of Lung Squamous Cell Carcinoma Recurrence With Self-supervised Learning [PDF]
Proceedings of The 5th International Conference on Medical Imaging
with Deep Learning, PMLR 172:1504-1522, 2022, 2022 Lung squamous cell carcinoma (LSCC) has a high recurrence and metastasis rate. Factors influencing recurrence and metastasis are currently unknown and there are no distinct histopathological or morphological features indicating the risks of recurrence and metastasis in LSCC.
arxiv
Changing cell mechanics -- a precondition for malignant transformation of oral squamous carcinoma cells [PDF]
, 2019 Oral squamous cell carcinomas (OSCC) are the 6th most common cancer and the diagnosis is often belated for a curative treatment. The reliable and early differentiation between healthy and diseased cells is the main aim of this study in order to improve the quality of the treatment and to understand tumour pathogenesis.
arxiv +1 more source