Results 61 to 70 of about 169,019 (308)

Self-Paced Learning With Diversity for Medical Image Segmentation by Using the Query-by-Committee and Dynamic Clustering Techniques

IEEE Access, 2021
Convolutional neural networks (CNNs), as a typical deep learning technique, have been widely used in image segmentation, but they often require a large amount of annotated data.
Xiaoying Pan, De Wei, Yizhe Zhao, Minjie Ma, Hao Wang   +4 more
doaj   +1 more source

Image segmentation, evaluation, and applications [PDF]

, 2010
This thesis aims to advance research in image segmentation by developing robust techniques for evaluating image segmentation algorithms. The key contributions of this work are as follows. First, we investigate the characteristics of existing measures for
McGuinness, Kevin
core  

Left-ventricle myocardium segmentation using a coupled level-set with a priori knowledge [PDF]

, 2006
This paper presents a coupled level-set segmentation of the myocardium of the left ventricle of the heart using a priori information. From a fast marching initialisation, two fronts representing the endocardium and epicardium boundaries of the left ...
Lynch, Michael, Ghita, Ovidiu, Whelan, Paul F.   +2 more
core   +1 more source

Valosin‐containing protein counteracts ATP‐driven dissolution of FUS condensates through its ATPase activity in vitro

FEBS Letters, EarlyView.
Biomolecular condensates formed by fused in sarcoma (FUS) are dissolved by high ATP concentrations yet persist in cells. Using a reconstituted system, we demonstrate that valosin‐containing protein (VCP), an AAA+ ATPase, counteracts ATP‐driven dissolution of FUS condensates through its D2 ATPase activity.
Hitomi Kimura, Shin‐ichi Tate, Kyota Yasuda   +2 more
wiley   +1 more source

TRAIL‐PEG‐Apt‐PLGA nanosystem as an aptamer‐targeted drug delivery system potential for triple‐negative breast cancer therapy using in vivo mouse model

Molecular Oncology, EarlyView.
Aptamers are used both therapeutically and as targeting agents in cancer treatment. We developed an aptamer‐targeted PLGA–TRAIL nanosystem that exhibited superior therapeutic efficacy in NOD/SCID breast cancer models. This nanosystem represents a novel biotechnological drug candidate for suppressing resistance development in breast cancer.
Gulen Melike Demirbolat, Aslihan Kucuk, Omer Erdogan, Samed Ozer, Bensu Kozan, Tugba Cuceli, Erkan Gumus, Evrim Cevik, Ozge Cevik   +8 more
wiley   +1 more source

Achieving the Way for Automated Segmentation of Nuclei in Cancer Tissue Images through Morphology-Based Approach: a Quantitative Evaluation [PDF]

, 2010
In this paper we address the problem of nuclear segmentation in cancer tissue images, that is critical for specific protein activity quantification and for cancer diagnosis and therapy.
MACII E., Ficarra, Elisa, Acquaviva, Andrea, Macii, E., Di Cataldo, Santa   +4 more
core   +1 more source

Mixed-block neural architecture search for medical image segmentation [PDF]

, 2022
Deep Neural Networks (DNNs) have the potential for making various clinical procedures more time-efficient by automating medical image segmentation. Due to their strong, in some cases human-level, performance, they have become the standard approach in ...
Dushatskiy, A. (author), Grewal, M. (author), Bosma, M.M.A. (Martijn), Dushatskiy, A. (Arkadiy), Bosman, P.A.N. (author), Bosman, P.A.N. (Peter), Alderliesten, T. (Tanja), Grewal, M. (Monika), Bosma, Martijn M.A. (author), Alderliesten, T. (author)   +9 more
core   +1 more source

CapsNet for medical image segmentation

Deep Learning for Medical Image Analysis, Elsevier/Academic Press (accepted)
Minh Q. Tran, Viet-Khoa Vo-Ho, Kyle Quinn, Hien Nguyen, Khoa Luu, Ngan Le   +5 more
openaire   +2 more sources

Network divergence analysis identifies adaptive gene modules and two orthogonal vulnerability axes in pancreatic cancer

Molecular Oncology, EarlyView.
Tumors contain diverse cellular states whose behavior is shaped by context‐dependent gene coordination. By comparing gene–gene relationships across biological contexts, we identify adaptive transcriptional modules that reorganize into distinct vulnerability axes.
Brian Nelson, Lyanne Delgado‐Coka, Natalia Marchenko, Luisa F. Escobar‐Hoyos, Kenneth R. Shroyer, Alisa Yurovsky, Trey Ideker, Gábor Balázsi, Thomas MacCarthy, Scott Powers   +9 more
wiley   +1 more source

Uncertainty-aware multi-view co-training for semi-supervised medical image segmentation and domain adaptation

, 2020
Although having achieved great success in medical image segmentation, deep learning-based approaches usually require large amounts of well-annotated data, which can be extremely expensive in the field of medical image analysis.
Yu, Zhiding, Liu, Fengze, Yu, Lequan, Yuille, Alan, Cai, Jinzheng, Xu, Daguang, Zhu, Zhuotun, Xia, Yingda, Yang, Dong, Roth, Holger   +9 more
core   +1 more source