Brain Tumor Detection Using 3D-UNet Segmentation Features and Hybrid Machine Learning Model by Bhargav Mallampati, Abid Ishaq, Furqan Rustam, Venu Kuthala, Sultan Alfarhood, Imran Ashraf

“…By training it on 3D-UNet segmentation features, we achieve a significant accuracy of 71% which surpasses existing state-of-the-art models that utilize 3D-UNet segmentation features.…”
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Automated segmentation of medical images for 3D printing – voxel centric processing of spatially textured voxels by Norman Cushing, Barry Fell, Kazi Safowan Shahed, Kevin W. Moser, Guha Manogharan

Subjects: “…3D printing…”
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Fast segmentation of stained nuclei in terabyte-scale, time resolved 3D microscopy image stacks. by Johannes Stegmaier, Jens C Otte, Andrei Kobitski, Andreas Bartschat, Ariel Garcia, G Ulrich Nienhaus, Uwe Strähle, Ralf Mikut

“…We evaluate the quality of the obtained segmentation results on a set of real and simulated benchmark images in 2D and 3D and show the algorithm's superior performance compared to other state-of-the-art algorithms. …”
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An Autism Spectrum Disorder Identification Method Based on 3D-CNN and Segmented Temporal Decision Network by Zhiling Liu, Ye Chen, Xinrui Dong, Jing Liu

“…This study aims to improve the ability to capture spatiotemporal dynamics of brain activity by proposing an advanced framework. (2) Methods: This study proposes an ASD recognition method that combines 3D Convolutional Neural Networks (3D-CNNs) and segmented temporal decision networks. …”
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CosPoint Transformer: Enhancing 3-D Semantic Segmentation With Cosine Similarity Attention and Cross-Attention by Thien Huynh-The, Minh-Thanh Le, Won Jae Ryu, Anh-Kiet Vo

Subjects: “…3-D sementic segmentation…”
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3D Segmentation and Visualization of Skin Vasculature Using Line-Field Confocal Optical Coherence Tomography by Oliver Mayer, Hanna Wirsching, Sophia Schlingmann, Julia Welzel, Sandra Schuh

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Application of Virtual Reality Technology and Unsupervised Video Object Segmentation Algorithm in 3D Model Modeling by Hui Yang, Qiuming Liu

“…The results show that the segmentation accuracy of this algorithm can reach more than 94%, which is about 9% higher than that of the FASTSEG method. 3D modeling technology is the foundation of 3D virtual scene; so, it is of practical significance to study the application of 3D modeling technology. …”
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MSTransBTS—A Novel Integration of Mamba with Swin Transformer for 3D Brain Tumour Segmentation by Jia Qin Ngu, Humaira Nisar, Chi-Yi Tsai

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High-precision segmentation and quantification of tunnel lining crack using an improved DeepLabV3+ by Zhutian Pan, Xuepeng Zhang, Yujing Jiang, Bo Li, Naser Golsanami, Hang Su, Yue Cai

“…We developed a novel approach called EDeepLab, aiming to achieve a higher precision detection and segmentation of lining surface crack. EDeepLab improves upon the original DeepLabV3+ framework by replacing its backbone network with an optimized lightweight EfficientNetV2. …”
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THE RESEARCH OF OSTEOPLASTIC PROPERTIES OF RESORBABLE POLY-3-HYDROXYBUTYRATE IN vIvO ON MODELS OF SEGMENTAL OSTEOTOMY by E. I. Shishatskaya, Yu. S. Vinnik, N. M. Markelova, I. V. Kamendov, S. I. Starosvetsky, V. A. Khorzhevsky, O. V. Peryanova, A. А. Shumilova, R. A. Pakhomova, E. S. Vasilenya, M. N. Kuznetsov

Subjects: “…plastic-3-hydroxybutyric acid…”
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MEASegNet: 3D U-Net with Multiple Efficient Attention for Segmentation of Brain Tumor Images by Ruihao Zhang, Peng Yang, Can Hu, Bin Guo

Subjects: “…3D U-Net…”
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A 7T MRI-Guided Learning Method for Automatic Hippocampal Subfield Segmentation on Routine 3T MRI by Linjin Wang, Jiangtao He, Guohong Geng, Lisha Zhong, Xinwei Li

“…Additionally, we further proposed an Online Knowledge Distillation (OLKD) method to distill detailed knowledge from 7T MRI into 3T MRI, enhancing the feature representation capability and robustness of the 3T MRI segmentation model. …”
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Multi-View Data Augmentation to Improve Wound Segmentation on 3D Surface Model by Deep Learning by R. Niri, E. Gutierrez, H. Douzi, Y. Lucas, S. Treuillet, B. Castaneda, I. Hernandez

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TRUSTED: The Paired 3D Transabdominal Ultrasound and CT Human Data for Kidney Segmentation and Registration Research by William Ndzimbong, Cyril Fourniol, Loic Themyr, Nicolas Thome, Yvonne Keeza, Benoît Sauer, Pierre-Thierry Piéchaud, Arnaud Méjean, Jacques Marescaux, Daniel George, Didier Mutter, Alexandre Hostettler, Toby Collins

“…We propose TRUSTED (the Tridimensional Renal Ultra Sound TomodEnsitometrie Dataset), comprising paired transabdominal 3DUS and CT kidney images from 48 human patients (96 kidneys), including segmentation, and anatomical landmark annotations by two experienced radiographers. …”
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A Comprehensive Review on Unsupervised Domain Adaptation for 3D Segmentation and Reconstruction in CT Urography Imaging by Shreya, Sushanth, Dasharathraj K. Shetty, Shreepathy Ranga Bhatta, Nikita Panwar

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Using Convolutional Neural Networks for Segmentation of Multiple Sclerosis Lesions in 3D Magnetic Resonance Imaging by Abdulsattar Abdullah Hamad, Mustafa Musa Jaber, Mohammed Altaf Ahmed, Ghaida Muttashar Abdulsahib, Osamah Ibrahim Khalaf, Zelalem Meraf

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Additive manufacturing of a 3D-segmented plastic scintillator detector for tracking and calorimetry of elementary particles by Tim Weber, Andrey Boyarintsev, Umut Kose, Botao Li, Davide Sgalaberna, Tetiana Sibilieva, Johannes Wüthrich, Siddartha Berns, Eric Boillat, Albert De Roeck, Till Dieminger, Matthew Franks, Boris Grynyov, Sylvain Hugon, Carsten Jaeschke, André Rubbia

“…Abstract Plastic scintillators, segmented into small, optically isolated voxels, are used for detecting elementary particles and provide reliable particle identification with nanosecond time resolution. …”
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MFSM-Net: Multimodal Feature Fusion for the Semantic Segmentation of Urban-Scale Textured 3D Meshes by Xinjie Hao, Jiahui Wang, Wei Leng, Rongting Zhang, Guangyun Zhang

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GIRH-Unet: Improved Residual Tobacco Segmentation Algorithm Based on GhostNetV3-Unet by Jianhua Ye, Yunda Zhang, Pan Li, Ze Guo

“…In this study, we propose an enhanced lightweight segmentation model, GhostNetV3-Unet, designed explicitly for residual tobacco segmentation. …”
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Post-disaster flooded region segmentation using DeepLabv3+ and unmanned aerial system imagery by Akila Agnes Sundaresan, Appadurai Arun Solomon

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