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The Brain Tumor Segmentation (BraTS) Challenge 2023: Glioma Segmentation in Sub-Saharan Africa Patient Population (BraTS-Africa)

Authors :
Adewole, Maruf
Rudie, Jeffrey D.
Gbadamosi, Anu
Toyobo, Oluyemisi
Raymond, Confidence
Zhang, Dong
Omidiji, Olubukola
Akinola, Rachel
Suwaid, Mohammad Abba
Emegoakor, Adaobi
Ojo, Nancy
Aguh, Kenneth
Kalaiwo, Chinasa
Babatunde, Gabriel
Ogunleye, Afolabi
Gbadamosi, Yewande
Iorpagher, Kator
Calabrese, Evan
Aboian, Mariam
Linguraru, Marius
Albrecht, Jake
Wiestler, Benedikt
Kofler, Florian
Janas, Anastasia
LaBella, Dominic
Kzerooni, Anahita Fathi
Li, Hongwei Bran
Iglesias, Juan Eugenio
Farahani, Keyvan
Eddy, James
Bergquist, Timothy
Chung, Verena
Shinohara, Russell Takeshi
Wiggins, Walter
Reitman, Zachary
Wang, Chunhao
Liu, Xinyang
Jiang, Zhifan
Familiar, Ariana
Van Leemput, Koen
Bukas, Christina
Piraud, Maire
Conte, Gian-Marco
Johansson, Elaine
Meier, Zeke
Menze, Bjoern H
Baid, Ujjwal
Bakas, Spyridon
Dako, Farouk
Fatade, Abiodun
Anazodo, Udunna C
Publication Year :
2023
Publisher :
arXiv, 2023.

Abstract

Gliomas are the most common type of primary brain tumors. Although gliomas are relatively rare, they are among the deadliest types of cancer, with a survival rate of less than 2 years after diagnosis. Gliomas are challenging to diagnose, hard to treat and inherently resistant to conventional therapy. Years of extensive research to improve diagnosis and treatment of gliomas have decreased mortality rates across the Global North, while chances of survival among individuals in low- and middle-income countries (LMICs) remain unchanged and are significantly worse in Sub-Saharan Africa (SSA) populations. Long-term survival with glioma is associated with the identification of appropriate pathological features on brain MRI and confirmation by histopathology. Since 2012, the Brain Tumor Segmentation (BraTS) Challenge have evaluated state-of-the-art machine learning methods to detect, characterize, and classify gliomas. However, it is unclear if the state-of-the-art methods can be widely implemented in SSA given the extensive use of lower-quality MRI technology, which produces poor image contrast and resolution and more importantly, the propensity for late presentation of disease at advanced stages as well as the unique characteristics of gliomas in SSA (i.e., suspected higher rates of gliomatosis cerebri). Thus, the BraTS-Africa Challenge provides a unique opportunity to include brain MRI glioma cases from SSA in global efforts through the BraTS Challenge to develop and evaluate computer-aided-diagnostic (CAD) methods for the detection and characterization of glioma in resource-limited settings, where the potential for CAD tools to transform healthcare are more likely.<br />Comment: arXiv admin note: text overlap with arXiv:2107.02314

Details

Database :
OpenAIRE
Accession number :
edsair.doi.dedup.....d637d7335f925326e8967c4d1f288f8b
Full Text :
https://doi.org/10.48550/arxiv.2305.19369