Vessel-CAPTCHA: An efficient learning framework for vessel annotation and segmentation

Dang, Vien Ngoc; Galati, Francesco; Cortese, Rosa; Giacomo, Giuseppe Di; Marconetto, Viola; Mathur, Prateek; Lekadir, Karim; Lorenzi, Marco; Prados, Ferrán; Zuluaga, María A.

doi:10.1016/j.media.2021.102263

Cited by 18 publications

(7 citation statements)

References 76 publications

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“… Fan et al (2022) implemented 3D segmentation for CMBs, but a DSC of only 72.00% was achieved. There have also been studies on brain vessels ( Dang et al, 2022 ), haemorrhage strokes ( Li et al, 2021a ) and white matter hyperintensities ( Li et al, 2018 ). In our study, an excellent performance, with a DSC of 87.93%, is achieved for the automatic segmentation of CMBs, as shown in Table 6 .…”

Section: Resultsmentioning

confidence: 99%

Construction of a Medical Micro-Object Cascade Network for Automated Segmentation of Cerebral Microbleeds in Susceptibility Weighted Imaging

Wei

Chen

Huang

et al. 2022

Front. Bioeng. Biotechnol.

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Aim: The detection and segmentation of cerebral microbleeds (CMBs) images are the focus of clinical diagnosis and treatment. However, segmentation is difficult in clinical practice, and missed diagnosis may occur. Few related studies on the automated segmentation of CMB images have been performed, and we provide the most effective CMB segmentation to date using an automated segmentation system.Materials and Methods: From a research perspective, we focused on the automated segmentation of CMB targets in susceptibility weighted imaging (SWI) for the first time and then constructed a deep learning network focused on the segmentation of micro-objects. We collected and marked clinical datasets and proposed a new medical micro-object cascade network (MMOC-Net). In the first stage, U-Net was utilized to select the region of interest (ROI). In the second stage, we utilized a full-resolution network (FRN) to complete fine segmentation. We also incorporated residual atrous spatial pyramid pooling (R-ASPP) and a new joint loss function.Results: The most suitable segmentation result was achieved with a ROI size of 32 × 32. To verify the validity of each part of the method, ablation studies were performed, which showed that the best segmentation results were obtained when FRN, R-ASPP and the combined loss function were used simultaneously. Under these conditions, the obtained Dice similarity coefficient (DSC) value was 87.93% and the F2-score (F2) value was 90.69%. We also innovatively developed a visual clinical diagnosis system that can provide effective support for clinical diagnosis and treatment decisions.Conclusions: We created the MMOC-Net method to perform the automated segmentation task of CMBs in an SWI and obtained better segmentation performance; hence, this pioneering method has research significance.

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Section: Resultsmentioning

confidence: 99%

Construction of a Medical Micro-Object Cascade Network for Automated Segmentation of Cerebral Microbleeds in Susceptibility Weighted Imaging

Wei

Chen

Huang

et al. 2022

Front. Bioeng. Biotechnol.

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“…In addition to hand biometric verification, liveness detection is added to the verification pipeline to improve security [7]. Vessel CAPTCHA [16] targets 3D brain vessel segmentation. It divides the image into 2D patches and users identify the patches containing a vessel or its part.…”

Section: Generic Image-based Captchasmentioning

confidence: 99%

Style matching CAPTCHA: match neural transferred styles to thwart intelligent attacks

et al. 2023

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“…From another perspective, the need for annotated images is not a decreasing one, since, as an example, machine (deep) learning algorithms require such knowledge for the training phase and/or other tasks (Vaughan, 2017;Russakovsky et al, 2015;Wu et al, 2020) as well as ground truth to evaluate models. Moreover, the CAPTCHA-based image annotation mechanics can be inspirational for designing innovative image annotation and segmentation frameworks, such as the recent work introduced in (Dang et al, 2022), Vessel-CAPTCHA, aimed to segment and annotate 3D brain vessel images by using a CAPTCHA-like mechanism.…”

Section: Research Motivationsmentioning

confidence: 99%

“…, 2020) as well as ground truth to evaluate models. Moreover, the CAPTCHA-based image annotation mechanics can be inspirational for designing innovative image annotation and segmentation frameworks, such as the recent work introduced in (Dang et al , 2022), Vessel-CAPTCHA, aimed to segment and annotate 3D brain vessel images by using a CAPTCHA-like mechanism.…”

Section: Research Motivationsmentioning

confidence: 99%

CAPTCHA for crowdsourced image annotation: directions and efficiency analysis

Moradi

Keyvanpour

2022

AJIM

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Purpose Image annotation plays an important role in image retrieval process, especially when it comes to content-based image retrieval. In order to compensate the intrinsic weakness of machines in performing cognitive task of (human-like) image annotation, leveraging humans’ knowledge and abilities in the form of crowdsourcing-based annotation have gained momentum. Among various approaches for this purpose, an innovative one is integrating the annotation process into the CAPTCHA workflow. In this paper, the current state of the research works in the field and experimental efficiency analysis of this approach are investigated.Design/methodology/approach At first, and with the aim of presenting a current state report of research studies in the field, a comprehensive literature review is provided. Then, several experiments and statistical analyses are conducted to investigate how CAPTCHA-based image annotation is reliable, accurate and efficient.Findings In addition to study of current trends and best practices for CAPTCHA-based image annotation, the experimental results demonstrated that despite some intrinsic limitations on leveraging the CAPTCHA as a crowdsourcing platform, when the challenge, i.e. annotation task, is selected and designed appropriately, the efficiency of CAPTCHA-based image annotation can outperform traditional approaches. Nonetheless, there are several design considerations that should be taken into account when the CAPTCHA is used as an image annotation platform.Originality/value To the best of the authors’ knowledge, this is the first study to analyze different aspects of the titular topic through exploration of the literature and experimental investigation. Therefore, it is anticipated that the outcomes of this study can draw a roadmap for not only CAPTCHA-based image annotation but also CAPTCHA-mediated crowdsourcing and even image annotation.

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Vessel-CAPTCHA: An efficient learning framework for vessel annotation and segmentation

Cited by 18 publications

References 76 publications

Construction of a Medical Micro-Object Cascade Network for Automated Segmentation of Cerebral Microbleeds in Susceptibility Weighted Imaging

Construction of a Medical Micro-Object Cascade Network for Automated Segmentation of Cerebral Microbleeds in Susceptibility Weighted Imaging

Style matching CAPTCHA: match neural transferred styles to thwart intelligent attacks

CAPTCHA for crowdsourced image annotation: directions and efficiency analysis

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