BackgroundRosacea is one of the most common cutaneous disorder characterized primarily by facial flushing, erythema, papules, pustules, telangiectases, and nasal swelling. Diagnosis of rosacea is principally done by a physical examination and a consistent patient history. However, qualitative human assessment is often subjective and suffers from a relatively high intra‐ and inter‐observer variability in evaluating patient outcomes.Materials and MethodsTo overcome these problems, we propose a quantitative and reproducible computer‐aided diagnosis system, Ros‐NET, which integrates information from different image scales and resolutions in order to identify rosacea lesions. This involves adaption of Inception‐ResNet‐v2 and ResNet‐101 to extract rosacea features from facial images. Additionally, we propose to refine the detection results by means of facial‐landmarks–based zones (ie, anthropometric landmarks) as regions of interest (ROI), which focus on typical areas of rosacea occurrence on a face.ResultsUsing a leave‐one‐patient‐out cross‐validation scheme, the weighted average Dice coefficients, in percentages, across all patients (N = 41) with 256 × 256 image patches are 89.8 ± 2.6% and 87.8 ± 2.4% with Inception‐ResNet‐v2 and ResNet‐101, respectively.ConclusionThe findings from this study support that pre‐trained networks trained via transfer learning can be beneficial in identifying rosacea lesions. Our future work will involve expanding the work to a larger database of cases with varying degrees of disease characteristics.

An adult presented with a 1-year history of worsening, painful lesions on the fingers of the right hand. The patient first noticed 1 lesion at the fingertip of the right third digit about 2 weeks after an injury to the hand. The lesion subsequently worsened and spread up this digit and affected the second digit as well. Treatment with multiple courses of antibiotics over the next few months for presumed cellulitis was followed by mild improvement but subsequent worsening after stopping antibiotic treatment. A diagnosis of psoriasis was made, based on a biopsy of a lesion on the patient's trunk, and treatment was begun with topical corticosteroids without any improvement after 2 months. There was no relevant medical or family history.Physical examination revealed extensive yellow-green crusting with underlying lakes of pus, a prominent surrounding and background erythema, and complete fingernail loss of the right first, second, and third digits, as well as the tip of the left first digit (Figure). The patient also had several well-demarcated erythematous plaques with overlying yellow hyperkeratosis and notable pus on the trunk, right knee, and left arm.Bacterialculturesofseveralpustulesweresterile.Giventhehistory ofantecedentfingertrauma,clinicalappearance,andbiopsyresults,the diagnosis of acrodermatitis continua of Hallopeau (ACH) was rendered. The patient was started on a regimen of oral methotrexate, 15 mg/wk, and betamethasone, 0.05%, ointment applied twice daily.Acrodermatitis continua of Hallopeau is a rare, chronic, and recalcitrant pustular eruption of the fingers and toes. The exact cause is unknown, but it is widely considered to be a localized variant of pustular psoriasis. 1 Most commonly occurring in middle-aged women, ACH often begins after localized trauma to a single digit with subsequent proximal spread. 2 It can be debilitating, often leading to loss of function in the affected digits and substantial morbidity.Diagnosis is primarily clinical, with additional testing with skin biopsy and microbial cultures performed primarily to exclude other conditions. Unfortunately, ACH is recalcitrant and chronic in nature, and it can transition into other forms of psoriasis. There are no standardized guidelines for treatment. Therapeutic options are similar to those of psoriasis and include both topical (eg, corticosteroids, calcineurin inhibitors) and systemic (eg, cyclosporine, methotrexate, and retinoids) medications. There has been some success with tumor necrosis factor inhibitors as well. 3

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