A lightweight neural network with multiscale feature enhancement for liver CT segmentation

<p dir="ltr">Segmentation of abdominal Computed Tomography (CT) scan is essential for analyzing, diagnosing, and treating visceral organ diseases (e.g., hepatocellular carcinoma). This paper proposes a novel neural network (Res-PAC-UNet) that employs a fixed-width residual UNet backb...

وصف كامل

محفوظ في:

التفاصيل البيبلوغرافية
المؤلف الرئيسي:	Mohammed Yusuf Ansari (16904523) (author)
مؤلفون آخرون:	Yin Yang (35103) (author), Shidin Balakrishnan (14150580) (author), Julien Abinahed (14151792) (author), Abdulla Al-Ansari (14150583) (author), Mohamed Warfa (18282250) (author), Omran Almokdad (18282253) (author), Ali Barah (14777533) (author), Ahmed Omer (18282256) (author), Ajay Vikram Singh (204056) (author), Pramod Kumar Meher (17316988) (author), Jolly Bhadra (14147823) (author), Osama Halabi (14158905) (author), Mohammad Farid Azampour (18282259) (author), Nassir Navab (6254012) (author), Thomas Wendler (13175656) (author), Sarada Prasad Dakua (14151789) (author)
منشور في:	2022
الموضوعات:	Biomedical and clinical sciences Clinical sciences Engineering Biomedical engineering Information and computing sciences Artificial intelligence Machine learning Abdominal Computed Tomography (CT) Segmentation Visceral organ diseases Hepatocellular carcinoma Neural network Res-PAC-UNet
الوسوم:	إضافة وسم لا توجد وسوم, كن أول من يضع وسما على هذه التسجيلة!

A lightweight neural network with multiscale feature enhancement for liver CT segmentation

مواد مشابهة