papers

Publications (14)

eess.IV2020

The state of the art in kidney and kidney tumor segmentation in contrast-enhanced CT imaging: Results of the KiTS19 Challenge

Nicholas Heller, Fabian Isensee, Klaus H. Maier-Hein +38

There is a large body of literature linking anatomic and geometric characteristics of kidney tumors to perioperative and oncologic outcomes. Semantic segmentation of these tumors a…

cs.CV2024

DomainVerse: A Benchmark Towards Real-World Distribution Shifts For Tuning-Free Adaptive Domain Generalization

Feng Hou, Jin Yuan, Ying Yang +7

Traditional cross-domain tasks, including domain adaptation and domain generalization, rely heavily on training model by source domain data. With the recent advance of vision-langu…

cs.CV2022

VerSe: A Vertebrae Labelling and Segmentation Benchmark for Multi-detector CT Images

Anjany Sekuboyina, Malek E. Husseini, Amirhossein Bayat +66

Vertebral labelling and segmentation are two fundamental tasks in an automated spine processing pipeline. Reliable and accurate processing of spine images is expected to benefit cl…

eess.IV2020

Modality-Pairing Learning for Brain Tumor Segmentation

Yixin Wang, Yao Zhang, Feng Hou +5

Automatic brain tumor segmentation from multi-modality Magnetic Resonance Images (MRI) using deep learning methods plays an important role in assisting the diagnosis and treatment…

cs.CL2023

How to Design Translation Prompts for ChatGPT: An Empirical Study

Yuan Gao, Ruili Wang, Feng Hou

The recently released ChatGPT has demonstrated surprising abilities in natural language understanding and natural language generation. Machine translation relies heavily on the abi…

cs.SD2023

PhasePerturbation: Speech Data Augmentation via Phase Perturbation for Automatic Speech Recognition

Chengxi Lei, Satwinder Singh, Feng Hou +2

Most of the current speech data augmentation methods operate on either the raw waveform or the amplitude spectrum of speech. In this paper, we propose a novel speech data augmentat…