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In this paper we introduce the Ladder Algorithm; a novel recurrent algorithm to detect repetitive structures in natural images with high accuracy using little training data. We then demonstrate the algorithm on the task of extracting…

计算机视觉与模式识别 · 计算机科学 2020-04-09 Rhydian Windsor , Amir Jamaludin

Magnetic Resonance Imaging (MRI) is pivotal in radiology, offering non-invasive and high-quality insights into the human body. Precise segmentation of MRIs into different organs and tissues would be highly beneficial since it would allow…

Vertebral morphological measurements are important across various disciplines, including spinal biomechanics and clinical applications, pre- and post-operatively. These measurements also play a crucial role in anthropological longitudinal…

计算机视觉与模式识别 · 计算机科学 2024-02-05 Ivanna Kramer , Vinzent Rittel , Lara Blomenkamp , Sabine Bauer , Dietrich Paulus

In this work, we propose to resolve the issue existing in current deep learning based organ segmentation systems that they often produce results that do not capture the overall shape of the target organ and often lack smoothness. Since…

计算机视觉与模式识别 · 计算机科学 2019-12-10 Yuan Xue , Hui Tang , Zhi Qiao , Guanzhong Gong , Yong Yin , Zhen Qian , Chao Huang , Wei Fan , Xiaolei Huang

Image segmentation is a long-standing challenge in computer vision, studied continuously over several decades, as evidenced by seminal algorithms such as N-Cut, FCN, and MaskFormer. With the advent of foundation models (FMs), contemporary…

计算机视觉与模式识别 · 计算机科学 2024-11-28 Tianfei Zhou , Wang Xia , Fei Zhang , Boyu Chang , Wenguan Wang , Ye Yuan , Ender Konukoglu , Daniel Cremers

Background: Accurate spinal structure measurement is crucial for assessing spine health and diagnosing conditions like spondylosis, disc herniation, and stenosis. Manual methods for measuring intervertebral disc height and spinal canal…

The segmentation of substantial brain lesions is a significant and challenging task in the field of medical image segmentation. Substantial brain lesions in brain imaging exhibit high heterogeneity, with indistinct boundaries between lesion…

计算机视觉与模式识别 · 计算机科学 2025-08-07 Hongming Wang , Yifeng Wu , Huimin Huang , Hongtao Wu , Jia-Xuan Jiang , Xiaodong Zhang , Hao Zheng , Xian Wu , Yefeng Zheng , Jinping Xu , Jing Cheng

Surgical segmentation is pivotal for scene understanding yet remains hindered by annotation scarcity and semantic inconsistency across diverse procedures. Existing approaches typically fine-tune natural foundation models (e.g., SAM) with…

计算机视觉与模式识别 · 计算机科学 2025-12-10 Qing Xu , Kun Yuan , Yuxiang Luo , Yuhao Zhai , Wenting Duan , Nassir Navab , Zhen Chen

Accurately segmenting 3D curvilinear structures in medical imaging remains challenging due to their complex geometry and the scarcity of diverse, large-scale datasets for algorithm development and evaluation. In this paper, we use dendritic…

Promptable segmentation foundation models have emerged as a transformative approach to addressing the diverse needs in medical images, but most existing models require expensive computing, posing a big barrier to their adoption in clinical…

Intervertebral discs (IVDs), as small joints lying between adjacent vertebrae, have played an important role in pressure buffering and tissue protection. The fully-automatic localization and segmentation of IVDs have been discussed in the…

图像与视频处理 · 电气工程与系统科学 2020-09-30 Chuanbo Wang , Ye Guo , Wei Chen , Zeyun Yu

Training segmentation models for medical images continues to be challenging due to the limited availability of data annotations. Segment Anything Model (SAM) is a foundation model that is intended to segment user-defined objects of interest…

计算机视觉与模式识别 · 计算机科学 2023-08-09 Maciej A. Mazurowski , Haoyu Dong , Hanxue Gu , Jichen Yang , Nicholas Konz , Yixin Zhang

Objective: The spinous process angle (SPA) is one of the essential parameters to denote three-dimensional (3-D) deformity of spine. We propose an automatic segmentation method based on Stacked Hourglass Network (SHN) to detect the spinous…

图像与视频处理 · 电气工程与系统科学 2021-05-25 Hong-Ye Zeng , Song-Han Ge , Yu-Chong Gao , De-Sen Zhou , Kang Zhou , Xu-Ming He , Edmond Lou , Rui Zheng

Recent advancements in foundation models, such as the Segment Anything Model (SAM), have shown strong performance in various vision tasks, particularly image segmentation, due to their impressive zero-shot segmentation capabilities.…

计算机视觉与模式识别 · 计算机科学 2025-05-12 Pengfei Gu , Haoteng Tang , Islam A. Ebeid , Jose A. Nunez , Fabian Vazquez , Diego Adame , Marcus Zhan , Huimin Li , Bin Fu , Danny Z. Chen

In clinical practice, regions of interest in medical imaging often need to be identified through a process of precise image segmentation. The quality of this image segmentation step critically affects the subsequent clinical assessment of…

图像与视频处理 · 电气工程与系统科学 2021-03-23 João B. S. Carvalho , João A. Santinha , Đorđe Miladinović , Joachim M. Buhmann

The landscape of publicly available vision foundation models (VFMs), such as CLIP and Segment Anything Model (SAM), is expanding rapidly. VFMs are endowed with distinct capabilities stemming from their pre-training objectives. For instance,…

Spinal degeneration plagues many elders, office workers, and even the younger generations. Effective pharmic or surgical interventions can help relieve degenerative spine conditions. However, the traditional diagnosis procedure is often too…

计算机视觉与模式识别 · 计算机科学 2021-11-11 Jiabo He , Wei Liu , Yu Wang , Xingjun Ma , Xian-Sheng Hua

Quantitative computed tomography (QCT) is a standard method to determine bone mineral density (BMD) in the spine. Traditionally single 8 - 10 mm thick slices have been analyzed only. Current spiral CT scanners provide true 3D acquisition…

计算机视觉与模式识别 · 计算机科学 2017-05-24 Andre Mastmeyer , Klaus Engelke , Christina Fuchs , Willi Kalender

Brain tumor segmentation presents a formidable challenge in the field of Medical Image Segmentation. While deep-learning models have been useful, human expert segmentation remains the most accurate method. The recently released Segment…

图像与视频处理 · 电气工程与系统科学 2023-10-11 Mohammad Peivandi , Jason Zhang , Michael Lu , Dongxiao Zhu , Zhifeng Kou