Cover Image

Test-Time Adaptation with SaLIP: A Cascade of SAM and CLIP for Zero shot Medical Image Segmentation

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Aleem, Sidra, Wang, Fangyijie, Maniparambil, Mayug, Arazo, Eric, Dietlmeier, Julia, Silvestre, Guenole, Curran, Kathleen, O'Connor, Noel E., Little, Suzanne
Format:	Preprint
Published:	2024
Subjects:	Computer Vision and Pattern Recognition Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

ConvLoRA and AdaBN based Domain Adaptation via Self-Training
by: Aleem, Sidra, et al.
Published: (2024)

Are Natural-Domain Foundation Models Effective for Accelerated Cardiac MRI Reconstruction?
by: Hashmi, Anam, et al.
Published: (2026)

Generative Diffusion Model Bootstraps Zero-shot Classification of Fetal Ultrasound Images In Underrepresented African Populations
by: Wang, Fangyijie, et al.
Published: (2024)

MiTU-Net: A fine-tuned U-Net with SegFormer backbone for segmenting pubic symphysis-fetal head
by: Wang, Fangyijie, et al.
Published: (2024)

Segmenting Fetal Head with Efficient Fine-tuning Strategies in Low-resource Settings: an empirical study with U-Net
by: Wang, Fangyijie, et al.
Published: (2024)

Semi-supervised Cervical Segmentation on Ultrasound by A Dual Framework for Neural Networks
by: Wang, Fangyijie, et al.
Published: (2025)

Evaluate Fine-tuning Strategies for Fetal Head Ultrasound Image Segmentation with U-Net
by: Wang, Fangyijie, et al.
Published: (2023)

Lightweight Framework for Automated Kidney Stone Detection using coronal CT images
by: Wang, Fangyijie, et al.
Published: (2023)

Dual Agreement Consistency Learning with Foundation Models for Semi-Supervised Fetal Heart Ultrasound Segmentation and Diagnosis
by: Wang, Fangyijie, et al.
Published: (2026)

Leveraging Information Divergence for Robust Semi-Supervised Fetal Ultrasound Image Segmentation
by: Wang, Fangyijie, et al.
Published: (2025)

Hold-One-Shot-Out (HOSO) for Validation-Free Few-Shot CLIP Adapters
by: Vorster, Chris, et al.
Published: (2026)

Entropy-Guided Agreement-Diversity: A Semi-Supervised Active Learning Framework for Fetal Head Segmentation in Ultrasound
by: Wang, Fangyijie, et al.
Published: (2026)

Ensemble Learning with Sparse Hypercolumns
by: Dietlmeier, Julia, et al.
Published: (2026)

Diffusion Model-based Data Augmentation Method for Fetal Head Ultrasound Segmentation
by: Wang, Fangyijie, et al.
Published: (2025)

Underrepresented in Foundation Model Pretraining Data? A One-Shot Probe
by: Vorster, Chris, et al.
Published: (2026)

Parameter-Free Bio-Inspired Channel Attention for Enhanced Cardiac MRI Reconstruction
by: Hashmi, Anam, et al.
Published: (2025)

Accelerating Cardiac MRI Reconstruction with CMRatt: An Attention-Driven Approach
by: Hashmi, Anam, et al.
Published: (2024)

Understanding Space Is Rocket Science -- Only Top Reasoning Models Can Solve Spatial Understanding Tasks
by: Hoehing, Nils, et al.
Published: (2025)

Fusing Radiomic Features with Deep Representations for Gestational Age Estimation in Fetal Ultrasound Images
by: Wang, Fangyijie, et al.
Published: (2025)

Pinpoint Counterfactuals: Reducing social bias in foundation models via localized counterfactual generation
by: Sirotkin, Kirill, et al.
Published: (2024)

Harnessing Frozen Unimodal Encoders for Flexible Multimodal Alignment
by: Maniparambil, Mayug, et al.
Published: (2024)

Cross-Modal Knowledge Distillation for PET-Free Amyloid-Beta Detection from MRI
by: Chiumento, Francesco, et al.
Published: (2026)

VLSM-Ensemble: Ensembling CLIP-based Vision-Language Models for Enhanced Medical Image Segmentation
by: Dietlmeier, Julia, et al.
Published: (2025)

TopoBench: Benchmarking LLMs on Hard Topological Reasoning
by: Maniparambil, Mayug, et al.
Published: (2026)

Understanding Task Aggregation for Generalizable Ultrasound Foundation Models
by: Wang, Fangyijie, et al.
Published: (2026)

Do Vision and Language Encoders Represent the World Similarly?
by: Maniparambil, Mayug, et al.
Published: (2024)

Enhancing Zero-Shot Anomaly Detection: CLIP-SAM Collaboration with Cascaded Prompts
by: Hou, Yanning, et al.
Published: (2025)

Machine Learning in Micromobility: A Systematic Review of Datasets, Techniques, and Applications
by: Yan, Sen, et al.
Published: (2025)

SynSacc: A Blender-to-V2E Pipeline for Synthetic Neuromorphic Eye-Movement Data and Sim-to-Real Spiking Model Training
by: Iddrisu, Khadija, et al.
Published: (2026)

Towards Label-Free Brain Tumor Segmentation: Unsupervised Learning with Multimodal MRI
by: Comas-Quiles, Gerard, et al.
Published: (2025)

An accurate detection is not all you need to combat label noise in web-noisy datasets
by: Albert, Paul, et al.
Published: (2024)

Breathing Green: Maximising Health and Environmental Benefits for Active Transportation Users Leveraging Large Scale Air Quality Data
by: Yan, Sen, et al.
Published: (2023)

Systematic Enumeration of Fundamental Quantities Involving Runs in Binary Strings
by: Balado, Félix, et al.
Published: (2026)

General Distributions of Number Representation Elements
by: Balado, Félix, et al.
Published: (2023)

ClipSAM: CLIP and SAM Collaboration for Zero-Shot Anomaly Segmentation
by: Li, Shengze, et al.
Published: (2024)

TokLIP: Marry Visual Tokens to CLIP for Multimodal Comprehension and Generation
by: Lin, Haokun, et al.
Published: (2025)

Evaluating Image-Based Face and Eye Tracking with Event Cameras
by: Iddrisu, Khadija, et al.
Published: (2024)

GenCLIP: Generalizing CLIP Prompts for Zero-shot Anomaly Detection
by: Kim, Donghyeong, et al.
Published: (2025)

CLIP-driven Zero-shot Learning with Ambiguous Labels
by: Fan, Jinfu, et al.
Published: (2026)

Explaining CLIP Zero-shot Predictions Through Concepts
by: Ozdemir, Onat, et al.
Published: (2026)