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Top Papers: Medizinische Bildsegmentierung (2026)

Die 26 meistzitierten Arbeiten zu Medizinische Bildsegmentierung aus dem Jahr 2026 (von 26 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.

#PaperZitationen
1

Alzheimer’s disease brain image segmentation using multi-feature fusion in 3D Rényi entropy model and quantum hybrid optimization

Mingyang Yu, Jiaqi Zhang, Lu Yu et al.

Artificial Intelligence Review

4
2

Enhancing efficiency in paediatric brain tumour segmentation using a pathologically diverse single-center clinical dataset

Arianna Piffer, Josef Alois Buchner, Antonio Giulio Gennari et al.

Neuro-Oncology Advances

2
3

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
4

Segmentation of objects in images using physical principles

Patrícia C. T. Gonçalves, João Manuel R. S. Tavares, Renato Natal Jorge

2
5

DATR: Diffusion-Based 3D Apple Tree Reconstruction Framework With Sparse-View

Tian Qiu, Alan Zoubi, Yiyuan Lin et al.

IEEE Robotics and Automation Letters

1
6

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
7

Geometric multi-instance learning for weakly supervised gastric cancer segmentation

Chenshen Huang, Haoyun Xia, Xi Xiao et al.

npj Digital Medicine

1
8

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
9

Frequency domain iterative clustering for boundary-preserving superpixel segmentation

Junbin Zhuang, Kun Wang, Zhe Yuan et al.

Applied Soft Computing

1
10

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
11

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
12

Efficient breast cancer segmentation via Brownian Bridge diffusion with semantic fusion strategy

Feiyan Feng, Tianyu Liu, Fulin Zheng et al.

Pattern Recognition

1
13

NucVerse3D: Generalizable 3D nuclear instance segmentation across heterogeneous microscopy modalities

Jorge Vergara, Cristian Pérez-Gallardo, Ricardo Velasco et al.

1
14

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
15

Anatomy-Guided Semi-Supervised Registration with Combined Rigid and Label Supervision for Improved Rib Deformation Consistency

Lukas Förner, Thomas Wendler

Lecture notes in computer science

1
16

Single pass Poisson disk sampling via circle packing

Jun Cui, Zeyu Li, Yuxiao Li et al.

Computers & Graphics

1
17

3D Medical Image Segmentation with 3D Modelling

Mária Ždímalová, Kristína Boratková, Sitár Viliam et al.

Bioengineering

1
18

Prioritized scanning: Combining spatial information multiple instance learning for computational pathology

Yuqi Zhang, Aoyu Li, Baoyu Liang et al.

Pattern Recognition

1
19

Learning deformable image registration with dilated attention transformer

Yungeng Zhang, yuan chang, Xiaohou Shi et al.

Knowledge-Based Systems

1
20

MoMIL: Multi-order enhanced multiple instance learning for computational pathology

Yuqi Zhang, Xiaoqian Zhang, Aoyu Li et al.

Image and Vision Computing

1
21

Hierarchical feature-guided dynamic collaborative learning transformer model for ventricular septal defect identification

Cheng Zhao, MD Weiling Chen, Peng Yang et al.

Neurocomputing

1
22

Shuffle Mamba: State Space Models with Random Shuffle for Multi-Modal Image Fusion

Ke Cao, Xuanhua He, Tao Hu et al.

IEEE Transactions on Circuits and Systems for Video Technology

1
23

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
24

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
25

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
26

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

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