Results 121 to 130 of about 823,307 (385)

Observations on the surgical pathology, selective lymphadenectomy, and classification of endometrial adenocarcinoma [PDF]

, 1952
Carl T. Javert, Karl Hofammann
openalex   +1 more source

Adenocarcinoma of the vagina. Association of maternal stilbestrol therapy with tumor appearance in young women.

New England Journal of Medicine, 1971
Although cancer of the vagina is rare and occurs principally in women over age 50 in the form of epidermoid carcinoma 8 girls (15-22) between 1966 and 1969 with adenocarcinoma of the vagina (clear-cell or endometrial) were seen at 2 Boston hospitals. The
A. Herbst, H. Ulfelder, D. Poskanzer
semanticscholar   +1 more source

Domain-stratified Training for Cross-organ and Cross-scanner Adenocarcinoma Segmentation in the COSAS 2024 Challenge [PDF]

arXiv
This manuscript presents an image segmentation algorithm developed for the Cross-Organ and Cross-Scanner Adenocarcinoma Segmentation (COSAS 2024) challenge. We adopted an organ-stratified and scanner-stratified approach to train multiple Upernet-based segmentation models and subsequently ensembled the results.
arxiv  

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

arXiv, 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  

Effects of simultaneous multislice acceleration on the stability of radiomics features in parametric maps of IVIM and DKI in uterine cervical cancer

Journal of Applied Clinical Medical Physics, EarlyView.
Abstract Purpose The aim of this study was to investigate the influence of the simultaneous multislice acceleration (SMS) technique as well as two‐dimensional (2D) and three‐dimensional (3D) tumor segmentations on radiomics features (RFs) within the parametric maps of cervical cancer, which were computed by intravoxel incoherent motion (IVIM) and ...
Shuangquan Ai, Wei Peng, Rong Hou, Huiting Zhang, Robert Grimm, Zilong Yuan, Yulin Liu   +6 more
wiley   +1 more source

Comparison of programmed death‐ligand 1 expression in adenocarcinoma and squamous cell carcinoma of the cervix in paraffin blocks of patients with cervical cancer

Cancer Reports
Aims Cervical cancer (CC) is a common malignancy in women, predominantly caused by human papillomavirus. The most subtypes are adenocarcinomas (AC) and squamous cell carcinomas (SCC), which show various features and treatment responses.
Maryam Sadat Hosseini, Fatemeh Shafizadeh, Mohammad Hashemi Bahremani, Farah Farzaneh, Tahereh Ashrafganjoei, Maliheh Arab, Maryam Talayeh, Fatemeh Jafari, Alireza Abdshah   +8 more
doaj   +1 more source

A Peculiar Case of Adenocarcinoma of the Body of the Uterus [PDF]

, 1900
Agnes C. Vietor
openalex   +1 more source

Novel CT radiomics models for the postoperative prediction of early recurrence of resectable pancreatic adenocarcinoma: A single‐center retrospective study in China

Journal of Applied Clinical Medical Physics, EarlyView.
Abstract Purpose To assess the predictive capability of CT radiomics features for early recurrence (ER) of pancreatic ductal adenocarcinoma (PDAC). Methods Postoperative PDAC patients were retrospectively selected, all of whom had undergone preoperative CT imaging and surgery. Both patients with resectable or borderline‐resectable pancreatic cancer met
Xinze Du, Yongsu Ma, Kexin Wang, Xiejian Zhong, Jianxin Wang, Xiaodong Tian, Xiaoying Wang, Yinmo Yang   +7 more
wiley   +1 more source

Domain and Content Adaptive Convolutions for Cross-Domain Adenocarcinoma Segmentation [PDF]

arXiv
Recent advances in computer-aided diagnosis for histopathology have been largely driven by the use of deep learning models for automated image analysis. While these networks can perform on par with medical experts, their performance can be impeded by out-of-distribution data.
arxiv  

Lung and Colon Cancer Histopathological Image Dataset (LC25000) [PDF]

arXiv, 2019
The field of Machine Learning, a subset of Artificial Intelligence, has led to remarkable advancements in many areas, including medicine. Machine Learning algorithms require large datasets to train computer models successfully. Although there are medical image datasets available, more image datasets are needed from a variety of medical entities ...
arxiv