Anatomically plausible segmentations: explicitly preserving topology through prior deformations by Wyburd, MK, Dinsdale, NK, Jenkinson, M, Namburete, AIL

“…Therefore, there is a need for new methods to focus on ensuring segmentations are topologically correct. In this work, we present TEDS-Net: a segmentation network that preserves anatomical topology whilst maintaining segmentation performance that is competitive with SOTA baselines. …”

Measurement of brain structures based on statistical and geometrical 3D segmentation by ángel, M, Ballester, G, Zisserman, A, Brady, M

“…In this paper we present a novel method for three-dimensional segmentation and measurement of volumetric data based on the combination of statistical and geometrical information. …”

The four facets of self-collection service for e-commerce delivery : conceptualisation and latent class analysis of user segments by Wang, Xueqin, Wong, Yiik Diew, Teo, Chee Chong, Yuen, Kum Fai, Feng, Xuehao

“…Based on the conceptualisation, five latent segments of the service are identified, which are labelled as Patrons, Traditionalists, Self-enhancers, Green-lovers and Haters (from the largest to the smallest segment). …”
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Optimum transmitter current distribution for dynamic wireless power transfer with segmented array by Jayathurathnage, Prasad Kumara Sampath, Alphones, Arokiaswami, Vilathgamuwa, D. Mahinda, Ong, Andrew

“…The misalignment problem is a major challenge in dynamic wireless power transfer systems with a segmented transmitter (Tx) array. Tx coils farther away from receiver (Rx) experience higher currents as compared to Tx coils nearer to Rx coil leading to higher losses and lower performances. …”
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Dual attention deep learning network for automatic steel surface defect segmentation by Pan, Yue, Zhang, Limao

“…Experimental results show that, compared with other deep learning models, DAN-DeepLabv3+ based on the Xception backbone exhibits the best segmentation performance under the mean intersection over union (IoU) of 89.95% and the frequency-weighted IoU of 97.34%. …”
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CRCNet: few-shot segmentation with cross-reference and region–global conditional networks by Liu, Weide, Zhang, Chi, Lin, Guosheng, Liu, Fayao

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Hybrid UNet transformer architecture for ischemic stoke segmentation with MRI and CT datasets by Soh, Wei Kwek, Rajapakse, Jagath Chandana

“…HUT achieves higher Dice scores and reduced Hausdorff Distance scores in single-modality and multi-modality lesion segmentation. HUT outperforms the state-the-art network SPiN in the single-modality MRI segmentation on Anatomical Tracings of lesion After Stroke (ATLAS) dataset by 4.84% of Dice score and a large margin of 40.7% in the Hausdorff Distance score. …”
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Automated detection and segmentation of vertebral bodies in volumetric abdominal magnetic resonance images by Lin, Dehui.

“…Detection and segmentation of the column of vertebral bodies are intermediate steps required to identify the bone marrow which is considered as the wrongly labeled visceral adipose tissue in the assessment of abdominal obesity. …”
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A study on Stevedoring companies and their operations in Singapore : break bulk shipping segment by Ng, Donovan Chun Hong

“…Just as how the break bulk shipping segment has not disappeared after containerization, but has changed in nature to become a specialised sector, handling goods which are challenging to transport in containers or where containerization does not represent a valid and cost-efficient mode of transport.…”
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Automatic segmentation of the choroid in enhanced depth imaging optical coherence tomography images by Tian, Jing, Marziliano, Pina, Baskaran, Mani, Tun, Tin Aung, Aung, Tin

“…This labeling process is tedious and subjective of inter-observer differences, hence, automatic segmentation of the choroid layer is highly desirable. …”
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Fast and accurate detection of Identical-By-Descent segment sharing in large genomic datasets by Saada, J

“…We introduce the basics of coalescent theory to understand IBD segments detection and then pro- vide an overview of a state-of-the art methods for detecting IBD segments, comparing the most commonly used and recent existing methods. …”

Rethinking semi-supervised medical image segmentation: a variance-reduction perspective by You, C, Dai, W, Min, Y, Liu, F, Clifton, DA, Zhou, SK, Staib, L, Duncan, JS

“…For medical image segmentation, contrastive learning is the dominant practice to improve the quality of visual representations by contrasting semantically similar and dissimilar pairs of samples. …”

OpenOFM: an open-source implementation of the multi-segment Oxford Foot Model by Dixon, P, Drew, E, McBride, S, Harrington, M, Stebbins, J, Zavatsky, A

“…Evaluation was conducted using the normalised root mean square error (NRMSE) between the inter-segment angles and arch heights of both implementations. …”

BiCoS: a bi-level co-segmentation method for image classification by Chai, Y, Lempitsky, V, Zisserman, A

“…The objective of this paper is the unsupervised segmentation of image training sets into foreground and background in order to improve image classification performance. …”

BLUE OCEAN SHIFT : BEYOND COMPETING - PROVEN STEPS TO INSPIRE CONFIDENCE AND SEIZE NEW GROWTH / by Kim, W. Chan, author 318022, Mauborgne, Renée, author 387551, Hachette Books Group (Online service) 647103

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BEACon : a boundary embedded attentional convolution network for point cloud instance segmentation by Liu, Tianrui, Cai, Yiyu, Zheng, Jianmin, Thalmann, Nadia Magnenat

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Tackling background ambiguities in multi-class few-shot point cloud semantic segmentation by Lai, Lvlong, Chen, Jian, Zhang, Chi, Zhang, Zehong, Lin, Guosheng, Wu, Qingyao

“…Few-shot point cloud semantic segmentation learns to segment novel classes with scarce labeled samples. …”
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Leveraging mixed data sources for enhanced road segmentation in synthetic aperture radar images by Lan, Tian, He, Shuting, Qing, Yuanyuan, Wen, Bihan

“…In this study, we tackle the task of road segmentation from Synthetic Aperture Radar (SAR) imagery, which is vital for remote sensing applications including urban planning and disaster management. …”
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A hybrid approach towards the segmentation of range images for 3-D object recognition by Lim, Alan Wui Tze.

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A binary level set model and some applications to Mumford-Shah image segmentation by Lie, Johan, Lysaker, Marius, Tai, Xue Cheng

“…We show numerical results using the method for segmentation of digital images.…”
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