Deep-learning (DL) algorithms are becoming the standard for processing ultrasound (US)
fetal images. A number of survey papers in the field is today available, but most of them are …

The task of multimodal cancer detection is to determine the locations and categories of
lesions by using different imaging techniques, which is one of the key research methods for …

Abstract Universal Lesion Detection (ULD) in computed tomography plays an essential role
in computer-aided diagnosis. Promising ULD results have been reported by multi-slice-input …

Deep learning is considered the leading artificial intelligence tool in image analysis in
general. Deep‐learning algorithms excel at image recognition, which makes them valuable …

Necrotising enterocolitis (NEC) is one of the most common diseases in neonates and
predominantly affects premature or very-low-birth-weight infants. Diagnosis is difficult and …

Ellipse detection is a fundamental task in object shape analysis. Under complex
environments, the traditional image processing based approaches may under-perform due …

Accurate and quick binuclear cell (BC) detection plays a significant role in predicting the risk
of leukemia and other malignant tumors. However, manual counting of BCs using …

Fetal echocardiography (ultrasound of the fetal heart) plays a vital role in identifying heart
defects, allowing clinicians to establish prenatal and postnatal management plans. Machine …

Abstract Universal Lesion Detection (ULD) in computed tomography (CT) plays an essential
role in computer-aided diagnosis. Promising ULD results have been reported by anchor …

Accurate detection of vulvovaginal candidiasis is critical for women's health, yet its sparse
distribution and visually ambiguous characteristics pose significant challenges for accurate …