Results 91 to 100 of about 169,019 (308)

MIRD-Net for Medical Image Segmentation [PDF]

, 2020
Medical image segmentation is a fundamental and challenging problem for analyzing medical images due to the approximate pixel values of adjacent tissues in boundary and the non-linear feature between pixels. Although fully convolutional neural networks such as U-Net has demonstrated impressive performance on medical image segmentation, distinguishing ...
Yongfeng Huang, Xueyang Li, Cairong Yan, Lihao Liu, Hao Dai   +4 more
openaire   +1 more source

Flow Enabled Target Capture Halbach‐based magnetic enrichment increases circulating tumor cell capture from blood in metastatic cancer patients

Molecular Oncology, EarlyView.
Pair‐wise comparison of the CellSearch and FETCH enrichment technologies for circulating tumor cells (CTCs) from metastatic breast, prostate, and small cell lung cancer patients shows an increased capture of CTCs using FETCH enrichment. The clinical implementation of circulating tumor cells (CTCs) as a predictive tool for therapy efficacy in the ...
Michiel Stevens, Anouk Mentink, Tom Niessink, Frank Coumans, Leonie Mekenkamp, Ruchi Bansal, Jeroen Hiltermann   +6 more
wiley   +1 more source

A novel quinazolinone insulin receptor inhibitor and its synergy with an EGFR inhibitor in glucose‐driven glioblastoma

Molecular Oncology, EarlyView.
The novel styrylquinazolinone‐based molecule W1B effectively suppresses glioblastoma by inhibiting IGF1R and EGFR. In high‐glucose microenvironments driving tumor resistance, W1B acts synergistically with the EGFR inhibitor dacomitinib. This combination safely blocks compensatory survival signaling in zebrafish xenograft models. Showcasing promising in
Patryk Rurka, Wioleta Cieślik, Wojciech Płaziński, Katarzyna Stępnik, Anna Boguszewska‐Czubara, Elżbieta Kot, Robert Musioł, Mateusz Jasica, Anna Mrozek‐Wilczkiewicz, Katarzyna Malarz   +9 more
wiley   +1 more source

Active contours with weighted external forces for medical image segmentation [PDF]

Parametric active contours have been widely used for image segmentation. However, high noise levels and weak edges are the most acute issues that hinder their performance, particularly in medical images.
Khadidos, Alaa, Sanchez Silva, Victor, Li, Chang-Tsun   +2 more
core  

Oncogenic DMTF1β promotes cancer cell motility by regulating autophagy through ULK1 stabilization

Molecular Oncology, EarlyView.
In the current study, we demonstrate that the oncogene DMTF1β regulates ULK1 stability by reducing its proteasomal degradation in cancer cells. This stabilization enables ULK1 to induce autophagy, which in turn facilitates cancer cell migration. Consequently, reduced DMTF1β levels lead to decreased autophagy and impaired cancer cell migration.
Jun Xu, Nicolas J. Niklaus, Anna M. Schläfli, Igor Tokarchuk, Magali Humbert, Federico La Manna, Bich Vu, David Maul, Ramin Radpour, Marianna Kruithof‐de Julio, Inti Zlobec, Jörn Dengjel, Bruce E. Torbett, Mario P. Tschan   +13 more
wiley   +1 more source

Advantages of transformer and its application for medical image segmentation: a survey

BioMedical Engineering OnLine
Purpose Convolution operator-based neural networks have shown great success in medical image segmentation over the past decade. The U-shaped network with a codec structure is one of the most widely used models.
Qiumei Pu, Zuoxin Xi, Shuai Yin, Zhe Zhao, Lina Zhao   +4 more
doaj   +1 more source

DA-TransUNet: integrating spatial and channel dual attention with transformer U-net for medical image segmentation

Frontiers in Bioengineering and Biotechnology
Accurate medical image segmentation is critical for disease quantification and treatment evaluation. While traditional U-Net architectures and their transformer-integrated variants excel in automated segmentation tasks. Existing models also struggle with
Guanqun Sun, Guanqun Sun, Yizhi Pan, Weikun Kong, Zichang Xu, Jianhua Ma, Teeradaj Racharak, Le-Minh Nguyen, Junyi Xin, Junyi Xin, Junyi Xin   +10 more
doaj   +1 more source

Performance characterization of clustering algorithms for colour image segmentation [PDF]

, 2006
This paper details the implementation of three traditional clustering techniques (K-Means clustering, Fuzzy C-Means clustering and Adaptive K-Means clustering) that are applied to extract the colour information that is used in the image segmentation ...
Ilea, Dana E., Ghita, Ovidiu, Whelan, Paul F.   +2 more
core  

Tumor B‐cell infiltration in platinum‐treated advanced muscle‐invasive urothelial carcinoma

Molecular Oncology, EarlyView.
Bladder tumors with higher pretreatment memory B‐cell infiltration were linked to longer survival after cisplatin chemotherapy, but not carboplatin. These tumors also showed more organized immune structures (tertiary lymphoid structures) and a shared pro‐inflammatory B‐cell‐rich community, suggesting that memory B cells may help identify patients most ...
Konrad Stawiski, Júlia Perera‐Bel, Alejo Rodriguez‐Vida, Nuria Juanpere, Jihyun Lee, Daniel E. Michaud, Jennifer L. Guerriero, Kent W. Mouw, Aristotelis Bamias, Filipe L. F. Carvalho, Joaquim Bellmunt   +10 more
wiley   +1 more source

Shortcut Learning in Medical Image Segmentation

Shortcut learning is a phenomenon where machine learning models prioritize learning simple, potentially misleading cues from data that do not generalize well beyond the training set. While existing research primarily investigates this in the realm of image classification, this study extends the exploration of shortcut learning into medical image ...
Manxi Lin, Nina Weng, Kamil Wojciech Mikolaj, Zahra Bashir, Morten Bo Søndergaard Svendsen, Martin Grønnebæk Tolsgaard, Anders Nymark Christensen, Aasa Feragen   +7 more
openaire   +4 more sources