Keywords: Psychiatric Disorders, Psychiatric Disorders
Motivation: The habenula is an important diencephalon structure related to pathophysiology of major depressive disorder (MDD), and segmenting Hb is challenging due to its low contrast and tiny size.
Goal(s): To establish a 3D cross-modality attention network (CMAN) for Hb segmentation and quantify its volume and T1 value in MDD patients compared to healthy controls (HCs).
Approach: We leveraged T1WI and T1 mapping from 3.0T MP2RAGE to train a CMAN model, assessing its accuracy and clinical relevance.
Results: The CMAN model achieved high accuracy in segmenting Hb, revealing significant differences in T1 values between MDD patients and HCs.
Impact: The habenula serves as a pivotal center modulating intricate behaviors encompassing emotions, motivation, and decision-making. Automatic and precise segmentation of habenula provides basis for further automatic quantitative analysis of habenula for major depression disorder studies.
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