Top Papers: Medizinische Bildsegmentierung (2026)

Die 19 meistzitierten Arbeiten zu Medizinische Bildsegmentierung aus dem Jahr 2026 (von 19 insgesamt).

Die automatische Bildsegmentierung ist eine Schlüsseltechnologie für die KI-gestützte Medizin. Algorithmen erkennen und markieren gezielt Organe, Tumore oder Gewebeveränderungen in CT-, MRT- und Ultraschallbildern. Das beschleunigt klinische Workflows und verbessert die Reproduzierbarkeit von Diagnosen. Diese Seite sammelt die wichtigsten Arbeiten aus diesem spezialisierten Forschungsfeld.

2024 2025 2026

#	Paper	Zitationen
1	Automated long axial field of view PET image processing and kinetic modelling with the TurBO toolbox Jouni Tuisku, Santeri Palonen, Henri Kärpijoki et al. European Journal of Nuclear Medicine and Molecular Imaging	2
2	Segmentation of objects in images using physical principles Patrícia C. T. Gonçalves, João Manuel R. S. Tavares, Renato Natal Jorge —	2
3	Dynamic Swin-UNet: a transformer-based adaptive framework for precise and efficient Alzheimer’s disease brain segmentation Marwa Ben Gara Ali, Abir Smiti Multimedia Tools and Applications	1
4	Diff4MMLiTS: Advanced Multimodal Liver Tumor Segmentation via Diffusion-Based Image Synthesis and Alignment Shiyun Chen, Li Lin, Pujin Cheng et al. Lecture notes in computer science	1
5	Geometric multi-instance learning for weakly supervised gastric cancer segmentation Chenshen Huang, Haoyun Xia, Xi Xiao et al. npj Digital Medicine	1
6	Frequency domain iterative clustering for boundary-preserving superpixel segmentation Junbin Zhuang, Kun Wang, Zhe Yuan et al. Applied Soft Computing	1
7	AutoPromptSeg: Automated Decoupling of Uncertainty Prompts with SAM for semi-supervised medical image segmentation Junan Zhu, Zhizhe Tang, Ma Ping et al. Computerized Medical Imaging and Graphics	1
8	Leveraging image transformation and optical flow for heterogeneous change detection under co-registration errors Yuli Sun, Lin Lei, Gangyao Kuang Gangyao Kuang Pattern Recognition	1
9	Efficient breast cancer segmentation via Brownian Bridge diffusion with semantic fusion strategy Feiyan Feng, Tianyu Liu, Fulin Zheng et al. Pattern Recognition	1
10	NucVerse3D: Generalizable 3D nuclear instance segmentation across heterogeneous microscopy modalities Jorge Vergara, Cristian Pérez-Gallardo, Ricardo Velasco et al. —	1
11	Artificial Intelligence-Assisted Image Segmentation in Scratch Wound Healing Assays Using Threshold and Level Set Methods Viviana Benfante, Muhammad Ali, Farhan Hai Khan et al. Lecture notes in computer science	1
12	Single pass Poisson disk sampling via circle packing Jun Cui, Zeyu Li, Yuxiao Li et al. Computers & Graphics	1
13	Prioritized scanning: Combining spatial information multiple instance learning for computational pathology Yuqi Zhang, Aoyu Li, Baoyu Liang et al. Pattern Recognition	1
14	Learning deformable image registration with dilated attention transformer Yungeng Zhang, yuan chang, Xiaohou Shi et al. Knowledge-Based Systems	1
15	MoMIL: Multi-order enhanced multiple instance learning for computational pathology Yuqi Zhang, Xiaoqian Zhang, Aoyu Li et al. Image and Vision Computing	1
16	EfficientNet-based multi-scale feature fusion with hybrid spatial-channel attention for precise liver and tumor segmentation in CT scans Javed Hossain Journal of Liver Transplantation	1
17	MFBRU-Net: Multi-scale feature fusion and boundary refining U-Net for medical image segmentation Han Gao, Xianran Zhang, Zhengpeng Li et al. Biomedical Signal Processing and Control	1
18	Segment Anything Model 2: An Application to 2D and 3D Medical Images Haoyu Dong, Hanxue Gu, Yaqian Chen et al. IEEE Transactions on Biomedical Engineering	1
19	EPSO-net: A multi-objective evolutionary neural architecture search with PSO-guided mutation fusion for explainable brain tumor segmentation Farhana Yasmin, Yu Xue, Mahade Hasan et al. Information Fusion	1

Top Papers: Medizinische Bildsegmentierung (2026)

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