We retrospectively included 100 cardiac amyloidosis (CA) and 217 hypertrophic cardiomyopathy (HCM) patients, aiming to elucidate the value of texture analysis (TA) in non-contrast T2-weighted CMR images of these patients. After the texture features were extracted, machine learning algorithms were used to select the optimal features. The results showed that TA was feasible and reproducible for detecting myocardial tissue alterations and differentiating CA from HCM, even in patients with similar hypertrophy. The radiomics model achieved a comparable diagnostic capacity to late gadolinium enhancement (LGE). Thus, TA might help eliminate the use of contrast agent in the diagnosis of these patients.