Md Mahfuzur Rahman Siddiquee
Overview
Explore the profile of Md Mahfuzur Rahman Siddiquee including associated specialties, affiliations and a list of published articles.
Author names and details appear as published. Due to indexing inconsistencies, multiple individuals may share a name, and a single author may have variations. MedLuna displays this data as publicly available, without modification or verification
Snapshot
Snapshot
Articles
11
Citations
1326
Followers
0
Related Specialties
Related Specialties
Top 10 Co-Authors
Top 10 Co-Authors
Published In
Published In
Affiliations
Affiliations
Soon will be listed here.
Recent Articles
1.
Payette K, Steger C, Licandro R, De Dumast P, Li H, Barkovich M, et al.
IEEE Trans Med Imaging
. 2024 Oct;
PP.
PMID: 39475746
Segmentation is a critical step in analyzing the developing human fetal brain. There have been vast improvements in automatic segmentation methods in the past several years, and the Fetal Brain...
2.
Siddiquee M, Shah J, Wu T, Chong C, Schwedt T, Dumkrieger G, et al.
IEEE Winter Conf Appl Comput Vis
. 2024 May;
2024:7558-7567.
PMID: 38720667
Harnessing the power of deep neural networks in the medical imaging domain is challenging due to the difficulties in acquiring large annotated datasets, especially for rare diseases, which involve high...
3.
Siddiquee M, Shah J, Wu T, Chong C, Schwedt T, Li B
Simul Synth Med Imaging
. 2024 May;
13570:43-54.
PMID: 38694707
Automated anomaly detection from medical images, such as MRIs and X-rays, can significantly reduce human effort in disease diagnosis. Owing to the complexity of modeling anomalies and the high cost...
4.
Shah J, Siddiquee M, Su Y, Wu T, Li B
IEEE Winter Conf Appl Comput Vis
. 2024 Apr;
2024:7867-7876.
PMID: 38606366
Age is one of the major known risk factors for Alzheimer's Disease (AD). Detecting AD early is crucial for effective treatment and preventing irreversible brain damage. Brain age, a measure...
5.
Payette K, Li H, De Dumast P, Licandro R, Ji H, Siddiquee M, et al.
Med Image Anal
. 2023 Jun;
88:102833.
PMID: 37267773
In-utero fetal MRI is emerging as an important tool in the diagnosis and analysis of the developing human brain. Automatic segmentation of the developing fetal brain is a vital step...
6.
Shah J, Siddiquee M, Krell-Roesch J, Syrjanen J, Kremers W, Vassilaki M, et al.
J Alzheimers Dis
. 2023 Mar;
92(4):1131-1146.
PMID: 36872783
There is a growing interest in the application of machine learning (ML) in Alzheimer's disease (AD) research. However, neuropsychiatric symptoms (NPS), frequent in subjects with AD, mild cognitive impairment (MCI),...
7.
Siddiquee M, Shah J, Chong C, Nikolova S, Dumkrieger G, Li B, et al.
Brain Commun
. 2023 Feb;
5(1):fcac311.
PMID: 36751567
Data-driven machine-learning methods on neuroimaging (e.g. MRI) are of great interest for the investigation and classification of neurological diseases. However, traditional machine learning requires domain knowledge to delineate the brain...
8.
Zhou Z, Sodha V, Siddiquee M, Feng R, Tajbakhsh N, Gotway M, et al.
Med Image Comput Comput Assist Interv
. 2020 Aug;
11767:384-393.
PMID: 32766570
Transfer learning from image to image has established as one of the most practical paradigms in deep learning for medical image analysis. However, to fit this paradigm, 3D imaging tasks...
9.
Zhou Z, Siddiquee M, Tajbakhsh N, Liang J
Deep Learn Med Image Anal Multimodal Learn Clin Decis Support (2018)
. 2020 Jul;
11045:3-11.
PMID: 32613207
In this paper, we present UNet++, a new, more powerful architecture for medical image segmentation. Our architecture is essentially a deeply-supervised encoder-decoder network where the encoder and decoder sub-networks are...
10.
Siddiquee M, Zhou Z, Tajbakhsh N, Feng R, Gotway M, Bengio Y, et al.
Proc IEEE Int Conf Comput Vis
. 2020 Jul;
2019:191-200.
PMID: 32612486
Generative adversarial networks (GANs) have ushered in a revolution in image-to-image translation. The development and proliferation of GANs raises an interesting question: can we train a GAN to remove an...