Results 41 to 50 of about 8,230,666 (286)

SEGMENTATION OF CANCER MASSES ON BREAST ULTRASOUND IMAGES USING MODIFIED U-NET

Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska, 2023
Breast cancer causes a huge number of women’s deaths every year. The accurate localization of a breast lesion is a crucial stage. The segmentation of breast ultrasound images participates in the improvement of the process of detection of breast ...
Ihssane Khallassi, My Hachem El Yousfi Alaoui, Abdelilah Jilbab   +2 more
doaj   +1 more source

Siamese Attention U-Net for Multi-Class Change Detection [PDF]

, 2022
Recent developments in deep learning have pushed the capabilities of pixel-wise change detection. This work introduces the winning solution of the DynamicEarthNet WeaklySupervised Multi-Class Change Detection Challenge held at the EARTHVISION Workshop in
Kondmann, Lukas, Cummings, Sol, Zhu, Xiao Xiang   +2 more
core   +1 more source

Reduction of decoder convolutional blocks in Attention Gate U-Net++ to enhance computational efficiency in automatic HR-CTV delineation on CT-based cervical cancer brachytherapy images

Journal of Associated Medical Sciences
Background: The contour of the high-risk clinical target volume (HR-CTV) is important in computed tomography (CT)-based cervical cancer brachytherapy to ensure adequate target tumor coverage while sparing radiation exposure to organs at risk (OARs ...
Thinnagit Srikhot, Chatrawut Pattaweerakul , Kamonchanok Nobphuek, Titipong Kaewlek   +3 more
doaj   +1 more source

Attention U-Net: Learning Where to Look for the Pancreas

CoRR, 2018
Accepted to published in MIDL'18 (Revised Version) / OpenReview link: https://openreview.net/forum?id ...
Ozan Oktay, Jo Schlemper, Loïc Le Folgoc, Matthew C. H. Lee, Mattias P. Heinrich, Kazunari Misawa, Kensaku Mori, Steven G. McDonagh 0001, Nils Y. Hammerla, Bernhard Kainz, Ben Glocker, Daniel Rueckert   +11 more
openaire   +2 more sources

Automated detection and segmentation of pleural effusion on ultrasound images using an Attention U-net. [PDF]

J Appl Clin Med Phys, 2023
BackgroundUltrasonic for detecting and evaluating pleural effusion is an essential part of the Extended Focused Assessment with Sonography in Trauma (E-FAST) in emergencies. Our study aimed to develop an Artificial Intelligence (AI) diagnostic model that
Huang L, Lin Y, Cao P, Zou X, Qin Q, Lin Z, Liang F, Li Z.   +7 more
europepmc   +2 more sources

Clinically Interpretable Nuclei Segmentation for Robust Histopathological Image Analysis

Applied Sciences
Background/Objectives: Accurate nuclear segmentation is a fundamental step in computational pathology, enabling reliable estimation of cellularity and nuclear morphology. However, segmentation models are typically evaluated under ideal imaging conditions,
Liana Stanescu, Cosmin Stoica Spahiu
doaj   +1 more source

AAU-Net: Attention-Based Asymmetric U-Net for Subject-Sensitive Hashing of Remote Sensing Images

, 2021
The prerequisite for the use of remote sensing images is that their security must be guaranteed. As a special subset of perceptual hashing, subject-sensitive hashing overcomes the shortcomings of the existing perceptual hashing that cannot distinguish ...
Yue Zeng, Jin Tian, Yueming Liu, Shiping Chen, Kaimeng Ding, Yu Wang   +5 more
core   +1 more source

Attention Guided 3D U-Net for KiTS19 [PDF]

Submissions to the 2019 Kidney Tumor Segmentation Challenge: KiTS19, 2019
We use a two-stage 3d U-Net model to predict the multi channels segmentations from coarse to fine. The second stage is guided by the predictions from the first stage. 1 Method We proposed a two stages method to segment CT image from coarse to fine.
Zhong, Zhusi, Zhang, Zhenxi, Jiao, Zhicheng   +2 more
openaire   +2 more sources

Ovarian Sex Cord Stromal Tumors in Children and Adolescents—The European Standard Clinical Practice Recommendations

Pediatric Blood &Cancer, EarlyView.
ABSTRACT As part of the European Cooperative Study Group for Paediatric Rare Tumours initiative, we developed standard clinical practice guidelines for ovarian sex cord stromal tumors, based on comprehensive national and international cohort analyses, literature review, and a final expert consensus conference.
Dominik T. Schneider, Kris‐Ann Schultz, Nora Schnitzler, Michael Abele, Tal Ben‐Ami, Ewa Bien, Gianni Bisogno, Ines B. Brecht, Maja Cesen, Andrea Ferrari, Michaela Kuhlen, Malgorzata A. Krawczyk, Ricardo Lopez‐Almaraz, Yves Reguerre, Calogero Virgone, Daniel Orbach   +15 more
wiley   +1 more source

DKA-U-Net: Dynamic-Kernel Attention U-Net for Brain Tumor Segmentation From MRI

IEEE Access
The precise delineation of tumor boundaries and the accurate segmentation of small tumor subregions are two pivotal factors influencing the performance of brain tumor segmentation from MRI.
Junjie Zhu, Heng Liu
doaj   +1 more source