Results 111 to 120 of about 1,762,979 (356)

Application of Generative Adversarial Networks Based on Global and Local Feature Information in Hippocampus Segmentation

Chinese Journal of Magnetic Resonance
Due to the complex structure and small size of the hippocampus, precise segmentation of the hippocampus remains challenging. To address this issue, this study proposes a generative adversarial network (GAN) based on global and local feature information ...
WEI Zhihong, KONG Xudong, KONG Yan, YAN Shiju, DING Yang, WEI Xianding, KONG Dong, YANG Bo   +7 more
doaj   +1 more source

Linear segmentation of discrete curves into blurred segments

Discrete Applied Mathematics, 2005
The concept of fuzzy segment is introduced, it allows the flexible segmentation of discrete curves, taking into account noise. Relying on an arithmetic definition of discrete lines [Réveilles 1991], it generalizes such lines, admitting that some points are missing. Thus, a larger class of objects is considered.
Debled-Rennesson, Isabelle, Rémy, Jean-Luc, Rouyer-Degli, Jocelyne   +2 more
openaire   +4 more sources

A large‐scale retrospective study in metastatic breast cancer patients using circulating tumour DNA and machine learning to predict treatment outcome and progression‐free survival

Molecular Oncology, EarlyView.
There is an unmet need in metastatic breast cancer patients to monitor therapy response in real time. In this study, we show how a noninvasive and affordable strategy based on sequencing of plasma samples with longitudinal tracking of tumour fraction paired with a statistical model provides valuable information on treatment response in advance of the ...
Emma J. Beddowes, Mario Ortega Duran, Solon Karapanagiotis, Alistair Martin, Meiling Gao, Riccardo Masina, Ramona Woitek, James Tanner, Fleur Tippin, Justine Kane, Jonathan Lay, Anja Brouwer, Stephen‐John Sammut, Suet‐Feung Chin, Davina Gale, Dana W. Y. Tsui, Sarah‐Jane Dawson, Nitzan Rosenfeld, Maurizio Callari, Oscar M. Rueda, Carlos Caldas   +20 more
wiley   +1 more source

Enchancing Lung Disease Classification through K-Means Clustering, Chan-Vese Segmentation, and Canny Edge Detection on X-Ray Segmented Images

JOIN: Jurnal Online Informatika
The lungs are one of the vital organs in the human body. Not only play a role in the respiratory system, the lungs are also responsible for the human circulatory system.
Joko Riyono, Christina Eni Pujiastuti, Sofia Debi Puspa, Supriyadi, Fayza Nayla Riyana Putri   +4 more
doaj   +1 more source

Multi‐omic characterization of consensus molecular subtype 1 (CMS1) colorectal cancer with dampened immune response improves precision medicine

Molecular Oncology, EarlyView.
This study highlights the importance of multi‐omic analyses in characterizing colorectal cancers. Indeed, our analysis revealed a rare CMS1 exhibiting dampened immune activation, including reduced PD‐1 expression, moderate CD8+ T‐cell infiltration, and suppressed JAK/STAT pathway.
Livia Concetti, Manuel Scimeca, Julia Bischof, Jonathan Woodsmith, Massimiliano Agostini, Cristina Fiorani, Yufang Shi, Eleonora Candi, Gerry Melino, Alessandro Mauriello, Giuseppe S. Sica   +10 more
wiley   +1 more source

HMA-Net: a hybrid mixer framework with multihead attention for breast ultrasound image segmentation

Frontiers in Artificial Intelligence
IntroductionBreast cancer is a severe illness predominantly affecting women, and in most cases, it leads to loss of life if left undetected. Early detection can significantly reduce the mortality rate associated with breast cancer. Ultrasound imaging has
Soumya Sara Koshy, L. Jani Anbarasi
doaj   +1 more source

Detecting homologous recombination deficiency for breast cancer through integrative analysis of genomic data

Molecular Oncology, EarlyView.
This study develops a semi‐supervised classifier integrating multi‐genomic data (1404 training/5893 validation samples) to improve homologous recombination deficiency (HRD) detection in breast cancer. Our method demonstrates prognostic value and predicts chemotherapy/PARP inhibitor sensitivity in HRD+ tumours.
Rong Zhu, Katherine Eason, Suet‐Feung Chin, Paul A. W. Edwards, Raquel Manzano Garcia, Richard Moulange, Jia Wern Pan, Soo Hwang Teo, Sach Mukherjee, Maurizio Callari, Carlos Caldas, Stephen‐John Sammut, Oscar M. Rueda   +12 more
wiley   +1 more source

Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm

IEEE Transactions on Medical Imaging, 2001
The finite mixture (FM) model is the most commonly used model for statistical segmentation of brain magnetic resonance (MR) images because of its simple mathematical form and the piecewise constant nature of ideal brain MR images.
Yongyue Zhang, M. Brady, Stephen M. Smith   +2 more
semanticscholar   +1 more source

Data‐driven discovery of gene expression markers distinguishing pediatric acute lymphoblastic leukemia subtypes

Molecular Oncology, EarlyView.
This study investigates gene expression differences between two major pediatric acute lymphoblastic leukemia (ALL) subtypes, B‐cell precursor ALL, and T‐cell ALL, using a data‐driven approach consisting of biostatistics and machine learning methods. Following analysis of a discovery dataset, we find a set of 14 expression markers differentiating the ...
Mona Nourbakhsh, Nikola Tom, Anna Schrøder Lassen, Helene Brasch Lind Petersen, Ulrik Kristoffer Stoltze, Karin Wadt, Kjeld Schmiegelow, Matteo Tiberti, Elena Papaleo   +8 more
wiley   +1 more source

Retinal Vessel Segmentation Based on a Lightweight U-Net and Reverse Attention

Mathematics
U-shaped architectures have achieved exceptional performance in medical image segmentation. Their aim is to extract features by two symmetrical paths: an encoder and a decoder.
Fernando Daniel Hernandez-Gutierrez, Eli Gabriel Avina-Bravo, Mario Alberto Ibarra-Manzano, Jose Ruiz-Pinales, Emmanuel Ovalle-Magallanes, Juan Gabriel Avina-Cervantes   +5 more
doaj   +1 more source